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67 [heteroglossia within a language the The Bushnell | Seating Charts novel since the seventeenth century] This latecomer reflects, in its stylistic structure, the struggle between two tendencies in the languages of European peoples: one a centralizing (unifying) tendency, the other a decentralizing tendency (that is, one that stratifies languages). The novel senses itself on the border between the completed, dominant literary language and Forest Snow Template,, the extraliterary languages that know heteroglossia . . . The Bushnell Center For The Performing Arts | Seating? . Powerpoint Template, | 02888? 67-8 Of course all these processes of Fashion Resume By Canva shift and Snow Backgrounds, renewal of the national language that are reflected by the novel do not bear an Fascinating Legal Resume 4 Legal Assistant, abstract linguistic character in Snow Backgrounds the novel: they are inseparable from Argument Essay Example. Example Argumentative Essay Middle, social and ideological struggle, from processes of Template, | 02888 evolution, and in Legal Resume Sample the renewal of society and the folk. 68 the problem of quotation. 69 is the author quoting with reverence or on the contrary with irony, with a smirk? 76 Thus every parody is an Forest Snow Backgrounds, intentional dialogized hybrid. Within it, languages and styles actively and mutually illuminate one another. Advertisement Essay Example? 77 an intense struggle and interanimation among languages. 82 to what extent the old and new worlds were characterized precisely by Snow | 02888 their own peculiar languages, by Template the images of language attached to each. Languages quarreled with each other, but this quarrel—like any quarrel among great and Forest Snow Powerpoint Backgrounds | 02888, significant cultural and historical forces—could not pass on Fascinating Examples Assistant, to a further phase by means of Template, Backgrounds abstract and rational dialogue, nor by a purely dramatic dialogue, but only by means of Assistant Job Description. Tips complexly dialogized hybrids. The great novels of the Renaissance were such hybrids, although stylistically they were monoglot. “Forms of Forest Template, | 02888 Time and of the Chronotope in the Novel”
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1 Computing with Language: Texts and Words. We're all very familiar with text, since we read and write it every day. Here we will treat text as raw data for the programs we write, programs that manipulate and analyze it in a variety of interesting ways. But before we can do this, we have to get started with the Python interpreter. One of the friendly things about Python is that it allows you to type directly into the interactive interpreter — the program that will be running your Python programs. You can access the Python interpreter using a simple graphical interface called the Interactive DeveLopment Environment (IDLE). Snow Powerpoint Template, | 02888! On a Mac you can find this under Applications > MacPython , and on Legal Resume Examples 4 Legal Windows under All Programs > Python . Under Unix you can run Python from the shell by typing idle (if this is not installed, try typing python ). The interpreter will print a blurb about your Python version; simply check that you are running Python 3.2 or later (here it is for 3.4.2): If you are unable to run the Forest Backgrounds, Python interpreter, you probably don't have Python installed correctly. Please visit http://python.org/ for - 12+ Free Pdf, Word,, detailed instructions. NLTK 3.0 works for Python 2.6 and 2.7.
If you are using one of these older versions, note that the Forest Powerpoint | 02888, / operator rounds fractional results downwards (so 1/3 will give you 0 ). In order to Resume Examples Resume Sample get the expected behavior of division you need to type: from __future__ import division. The prompt indicates that the Python interpreter is now waiting for input. Forest Template, Backgrounds | 02888! When copying examples from this book, don't type the yourself. Now, let's begin by using Python as a calculator: Once the interpreter has finished calculating the answer and displaying it, the prompt reappears. This means the Python interpreter is waiting for The Bushnell For The Performing Arts | Seating, another instruction. Your Turn: Enter a few more expressions of Snow | 02888, your own. You can use asterisk ( * ) for Advertisement Essay Example, multiplication and slash ( / ) for division, and Forest Powerpoint | 02888 parentheses for bracketing expressions. The preceding examples demonstrate how you can work interactively with the Python interpreter, experimenting with various expressions in The Creative the language to Forest Backgrounds see what they do. Job Description. Resume! Now let's try a nonsensical expression to see how the interpreter handles it:
This produced a syntax error . In Python, it doesn't make sense to Template, | 02888 end an instruction with a plus sign. The Python interpreter indicates the line where the problem occurred (line 1 of stdin , which stands for standard input). Now that we can use the Service Level - 12+ Pdf, Psd Documents, Python interpreter, we're ready to start working with language data. Before going further you should install NLTK 3.0, downloadable for free from http://nltk.org/ . Follow the instructions there to download the version required for your platform. Once you've installed NLTK, start up the Python interpreter as before, and install the Forest Snow Template, Backgrounds | 02888, data required for the book by typing the following two commands at the Python prompt, then selecting the book collection as shown in Argument Essay Example. Argumentative Essay 1.1. Figure 1.1 : Downloading the Forest Powerpoint Template, Backgrounds, NLTK Book Collection: browse the available packages using nltk.download() . Resume Examples Assistant Sample! The Collections tab on the downloader shows how the packages are grouped into sets, and you should select the line labeled book to obtain all data required for the examples and Snow Powerpoint Template, | 02888 exercises in this book.
It consists of about 30 compressed files requiring about The Creative Entrepreneur 8 Tips For Startup 100Mb disk space. The full collection of data (i.e., all in the downloader) is nearly ten times this size (at the time of writing) and continues to expand. Once the data is Snow Powerpoint Template, Backgrounds downloaded to your machine, you can load some of Example, it using the Python interpreter. The first step is to type a special command at the Python prompt which tells the interpreter to Forest Powerpoint Template, | 02888 load some texts for The Creative Checklist: 8 Tips Success | Made, us to explore: from Forest nltk.book import * . This says from NLTK's book module, load all items. The book module contains all the data you will need as you read this chapter. After printing a welcome message, it loads the text of several books (this will take a few seconds).
Here's the command again, together with the output that you will see. Take care to get spelling and punctuation right, and remember that you don't type the . Any time we want to find out The Bushnell Center | Seating about these texts, we just have to Snow Template, enter their names at The Creative For Startup Success, the Python prompt: Now that we can use the Python interpreter, and have some data to work with, we're ready to Forest Snow Powerpoint Template, Backgrounds | 02888 get started. There are many ways to examine the context of a text apart from Service Level Agreement - 12+ Free Psd Documents simply reading it. A concordance view shows us every occurrence of a given word, together with some context.
Here we look up the Powerpoint Template, | 02888, word monstrous in Moby Dick by entering text1 followed by a period, then the term concordance , and Example Argumentative then placing monstrous in parentheses: The first time you use a concordance on Snow Backgrounds a particular text, it takes a few extra seconds to build an index so that subsequent searches are fast. Your Turn: Try searching for other words; to save re-typing, you might be able to use up-arrow, Ctrl-up-arrow or Alt-p to access the The Creative Entrepreneur Success, previous command and modify the word being searched. You can also try searches on some of the other texts we have included. For example, search Sense and Sensibility for the word affection , using text2.concordance( affection ) . Search the Snow Backgrounds | 02888, book of Genesis to find out Argument Essay Middle how long some people lived, using text3.concordance( lived ) . You could look at text4 , the Inaugural Address Corpus , to see examples of English going back to 1789, and Snow Powerpoint Backgrounds | 02888 search for words like nation , terror , god to see how these words have been used differently over time. We've also included text5 , the The Creative Checklist: 8 Tips, NPS Chat Corpus : search this for unconventional words like im , ur , lol . (Note that this corpus is uncensored!) Once you've spent a little while examining these texts, we hope you have a new sense of the richness and diversity of language. In the next chapter you will learn how to access a broader range of text, including text in languages other than English. A concordance permits us to see words in context. For example, we saw that monstrous occurred in Forest Template, | 02888 contexts such as the ___ pictures and a ___ size . What other words appear in a similar range of contexts?
We can find out by appending the term similar to Service Level - 12+ Free Psd Documents the name of the text in question, then inserting the Forest Powerpoint Template,, relevant word in The Bushnell Center | Seating parentheses: Observe that we get different results for | 02888, different texts. Example! Austen uses this word quite differently from Melville; for Snow Template, Backgrounds | 02888, her, monstrous has positive connotations, and sometimes functions as an intensifier like the Checklist: | Made, word very . The term common_contexts allows us to examine just the contexts that are shared by two or more words, such as monstrous and very . We have to enclose these words by square brackets as well as parentheses, and separate them with a comma: Your Turn: Pick another pair of words and compare their usage in two different texts, using the similar() and common_contexts() functions. It is one thing to automatically detect that a particular word occurs in a text, and to display some words that appear in Forest Powerpoint Template, | 02888 the same context. However, we can also determine the location of a word in Examples 4 Legal Assistant Resume the text: how many words from the beginning it appears. This positional information can be displayed using a dispersion plot . Each stripe represents an instance of Forest Snow Template,, a word, and Argument Essay Argumentative Essay Middle School each row represents the entire text. Snow Powerpoint Template, Backgrounds | 02888! In 1.2 we see some striking patterns of word usage over the last 220 years (in an artificial text constructed by joining the texts of the Inaugural Address Corpus end-to-end).
You can produce this plot as shown below. You might like to try more words (e.g., liberty , constitution ), and different texts. Can you predict the dispersion of a word before you view it? As before, take care to get the The Creative Checklist: For Startup, quotes, commas, brackets and parentheses exactly right. Figure 1.2 : Lexical Dispersion Plot for Words in U.S.
Presidential Inaugural Addresses: This can be used to investigate changes in language use over time. Important: You need to have Python's NumPy and Matplotlib packages installed in Snow order to produce the graphical plots used in this book. Please see http://nltk.org/ for The Bushnell For The, installation instructions. You can also plot the frequency of word usage through time using https://books.google.com/ngrams. Now, just for fun, let's try generating some random text in the various styles we have just seen. To do this, we type the name of the Powerpoint Template, | 02888, text followed by the term generate . Advertisement Example! (We need to Forest Snow Template, | 02888 include the parentheses, but there's nothing that goes between them.) The generate() method is Administrative Assistant Job Description. Best Tips not available in NLTK 3.0 but will be reinstated in a subsequent version. The most obvious fact about texts that emerges from the preceding examples is that they differ in the vocabulary they use. In this section we will see how to Template, | 02888 use the computer to count the words in For The Performing Arts Charts a text in a variety of useful ways. As before, you will jump right in and experiment with the Python interpreter, even though you may not have studied Python systematically yet.
Test your understanding by modifying the examples, and trying the exercises at the end of the chapter. Let's begin by finding out the length of a text from start to finish, in terms of the words and punctuation symbols that appear. We use the term len to Forest Powerpoint Backgrounds | 02888 get the length of Level Agreement - 12+ Pdf, Psd Documents, something, which we'll apply here to Forest Snow Template, | 02888 the book of Genesis: So Genesis has 44,764 words and punctuation symbols, or tokens. A token is the technical name for a sequence of characters — such as hairy , his , or :) — that we want to treat as a group. When we count the number of Argument Essay Example. Argumentative Essay School, tokens in Forest Snow Template, a text, say, the phrase to Argument Essay Argumentative Essay Middle School be or not to Snow Powerpoint Template, | 02888 be , we are counting occurrences of these sequences. Thus, in our example phrase there are two occurrences of to , two of be , and one each of or and not . But there are only four distinct vocabulary items in this phrase. The Bushnell For The Arts Charts! How many distinct words does the book of Powerpoint Backgrounds | 02888, Genesis contain? To work this out in Python, we have to Medical Administrative Assistant pose the question slightly differently. The vocabulary of a text is just the set of tokens that it uses, since in a set, all duplicates are collapsed together.
In Python we can obtain the Forest Template, Backgrounds | 02888, vocabulary items of text3 with the command: set(text3) . When you do this, many screens of words will fly past. Now try the Legal Resume 4 Legal Resume, following: By wrapping sorted() around the Forest Snow Template,, Python expression set(text3) , we obtain a sorted list of vocabulary items, beginning with various punctuation symbols and continuing with words starting with A . All capitalized words precede lowercase words. We discover the size of the vocabulary indirectly, by asking for the number of items in the set, and again we can use len to obtain this number . Although it has 44,764 tokens, this book has only 2,789 distinct words, or word types. A word type is the form or spelling of the word independently of Entrepreneur 8 Tips For Startup Success, its specific occurrences in a text — that is, the word considered as a unique item of vocabulary. Our count of 2,789 items will include punctuation symbols, so we will generally call these unique items types instead of word types.
Now, let's calculate a measure of the Snow Backgrounds | 02888, lexical richness of the text. The next example shows us that the Assistant, number of distinct words is Forest Powerpoint | 02888 just 6% of the total number of words, or equivalently that each word is Center Performing Arts | Seating used 16 times on average (remember if you're using Python 2, to start with from Snow Template, Backgrounds __future__ import division ). Next, let's focus on particular words. We can count how often a word occurs in a text, and compute what percentage of the text is taken up by a specific word: Your Turn: How many times does the word lol appear in text5 ? How much is this as a percentage of the total number of Fascinating 4 Legal Resume Sample, words in this text?
You may want to repeat such calculations on several texts, but it is Forest Powerpoint Backgrounds tedious to keep retyping the formula. Instead, you can come up with your own name for a task, like lexical_diversity or percentage, and associate it with a block of code. Now you only have to type a short name instead of Administrative Assistant Job Description. Best Tips, one or more complete lines of Python code, and Forest Snow Backgrounds you can re-use it as often as you like. Examples 4 Legal Assistant Resume! The block of code that does a task for us is called a function , and we define a short name for our function with the keyword def . The next example shows how to define two new functions, lexical_diversity() and percentage() : The Python interpreter changes the Snow | 02888, prompt from to . after encountering the The Bushnell Center For The Performing | Seating, colon at the end of the first line. The . prompt indicates that Python expects an indented code block to appear next. It is up to you to do the indentation, by typing four spaces or hitting the Forest Snow Template, Backgrounds, tab key. Medical Assistant Job Description.! To finish the indented block just enter a blank line.
In the Backgrounds, definition of lexical_diversity() , we specify a parameter named text . This parameter is a placeholder for the actual text whose lexical diversity we want to compute, and reoccurs in Fascinating Legal Resume Examples Assistant Sample the block of code that will run when the Forest | 02888, function is used . Resume 4 Legal Resume! Similarly, percentage() is defined to Forest Snow Template, take two parameters, named count and total . Once Python knows that lexical_diversity() and percentage() are the names for The Bushnell Performing Arts Charts, specific blocks of code, we can go ahead and use these functions: To recap, we use or call a function such as lexical_diversity() by typing its name, followed by an open parenthesis, the name of the Forest Snow Backgrounds | 02888, text, and then a close parenthesis. These parentheses will show up often; their role is to separate the Entrepreneur For Startup, name of a task — such as lexical_diversity() — from the data that the task is to be performed on Snow Powerpoint | 02888 — such as text3 . The data value that we place in Advertisement the parentheses when we call a function is an argument to the function. You have already encountered several functions in this chapter, such as len() , set() , and sorted() . By convention, we will always add an Forest Snow Powerpoint Backgrounds | 02888, empty pair of parentheses after a function name, as in len() , just to make clear that what we are talking about is a function rather than some other kind of Python expression. Functions are an important concept in programming, and we only mention them at the outset to give newcomers a sense of the power and creativity of programming. Don't worry if you find it a bit confusing right now. Later we'll see how to use functions when tabulating data, as in Argument Essay Example Essay 1.1. Forest Template, Backgrounds! Each row of the table will involve the same computation but with different data, and we'll do this repetitive work using a function. Lexical Diversity of Various Genres in the Brown Corpus.
2 A Closer Look at Python: Texts as Lists of Words. You've seen some important elements of the Python programming language. Let's take a few moments to review them systematically. What is a text? At one level, it is a sequence of symbols on The Creative Entrepreneur Checklist: | Made a page such as this one. Forest Powerpoint Template,! At another level, it is a sequence of Service Agreement Word,, chapters, made up of a sequence of sections, where each section is a sequence of paragraphs, and so on. However, for our purposes, we will think of a text as nothing more than a sequence of words and punctuation. Here's how we represent text in Python, in this case the opening sentence of Moby Dick : After the prompt we've given a name we made up, sent1 , followed by the equals sign, and then some quoted words, separated with commas, and surrounded with brackets. This bracketed material is known as a list in Python: it is Forest how we store a text. We can inspect it by typing the name . We can ask for its length . We can even apply our own lexical_diversity() function to it . Some more lists have been defined for Resume Examples Assistant, you, one for the opening sentence of each of our texts, sent2 … sent9 . Snow Template, Backgrounds | 02888! We inspect two of them here; you can see the Advertisement Example, rest for yourself using the Python interpreter (if you get an error which says that sent2 is not defined, you need to first type from Snow Backgrounds nltk.book import * ). Your Turn: Make up a few sentences of your own, by typing a name, equals sign, and Essay Example Argumentative a list of words, like this: ex1 = [ 'Monty' , 'Python' , 'and' , 'the' , 'Holy' , 'Grail' ] . Snow Powerpoint Backgrounds | 02888! Repeat some of the other Python operations we saw earlier in 1, e.g., sorted(ex1) , len(set(ex1)) , ex1.count( 'the' ) . A pleasant surprise is that we can use Python's addition operator on lists.
Adding two lists creates a new list with everything from the Legal 4 Legal Assistant Resume, first list, followed by Snow Template, Backgrounds everything from the second list: This special use of the addition operation is called concatenation ; it combines the lists together into a single list. We can concatenate sentences to build up a text. We don't have to Center For The | Seating literally type the lists either; we can use short names that refer to pre-defined lists. What if we want to add a single item to a list? This is known as appending . When we append() to a list, the list itself is updated as a result of the operation. As we have seen, a text in Python is a list of words, represented using a combination of brackets and quotes. Forest Powerpoint Backgrounds | 02888! Just as with an ordinary page of text, we can count up the Assistant Job Description. Best Tips, total number of words in text1 with len(text1) , and count the occurrences in | 02888 a text of a particular word — say, 'heaven' — using text1.count( 'heaven' ) . With some patience, we can pick out the 1st, 173rd, or even 14,278th word in a printed text. Analogously, we can identify the The Bushnell Performing Arts | Seating, elements of a Python list by their order of occurrence in the list.
The number that represents this position is the Forest Snow Template,, item's index . We instruct Python to Example show us the item that occurs at an index such as 173 in a text by writing the name of the text followed by the index inside square brackets: We can do the Snow | 02888, converse; given a word, find the index of when it first occurs: Indexes are a common way to access the words of Assistant Best Resume Tips, a text, or, more generally, the elements of any list. Python permits us to access sublists as well, extracting manageable pieces of language from large texts, a technique known as slicing . Indexes have some subtleties, and Forest Powerpoint we'll explore these with the Agreement - 12+ Free Word, Psd Documents, help of an artificial sentence: Notice that our indexes start from Powerpoint | 02888 zero: sent element zero, written sent , is the first word, 'word1' , whereas sent element 9 is Legal Resume Assistant Resume Sample 'word10' . Snow! The reason is Advertisement Example simple: the moment Python accesses the content of a list from the computer's memory, it is already at the first element; we have to tell it how many elements forward to go. Thus, zero steps forward leaves it at the first element. This practice of counting from zero is initially confusing, but typical of modern programming languages. You'll quickly get the hang of it if you've mastered the system of counting centuries where 19XY is a year in the 20th century, or if you live in a country where the floors of a building are numbered from 1, and so walking up n-1 flights of Forest Snow Backgrounds | 02888, stairs takes you to level n . Now, if we accidentally use an index that is The Creative Entrepreneur Checklist: Success | Made too large, we get an error: This time it is Powerpoint Template, | 02888 not a syntax error, because the program fragment is syntactically correct.
Instead, it is a runtime error , and it produces a Traceback message that shows the context of the error, followed by the name of the error, IndexError , and a brief explanation. Let's take a closer look at Medical Administrative Assistant Resume, slicing, using our artificial sentence again. Powerpoint Template,! Here we verify that the slice 5:8 includes sent elements at indexes 5, 6, and Center Arts Charts 7: By convention, m:n means elements m … n-1 . As the next example shows, we can omit the Powerpoint Template,, first number if the slice begins at the start of the list , and we can omit the second number if the slice goes to the end : We can modify an Advertisement Essay Example, element of a list by Forest Snow Powerpoint assigning to one of its index values. In the next example, we put sent on the left of the equals sign . We can also replace an entire slice with new material . A consequence of this last change is that the list only has four elements, and Entrepreneur Success | Made accessing a later value generates an error . Your Turn: Take a few minutes to Forest Powerpoint define a sentence of your own and Entrepreneur Checklist: For Startup Success modify individual words and groups of words (slices) using the same methods used earlier.
Check your understanding by trying the exercises on lists at Forest Snow Backgrounds | 02888, the end of this chapter. From the start of 1, you have had access to texts called text1 , text2 , and so on. It saved a lot of typing to be able to refer to a 250,000-word book with a short name like this! In general, we can make up names for Legal Examples, anything we care to calculate. We did this ourselves in the previous sections, e.g., defining a variable sent1 , as follows: Such lines have the form: variable = expression . Python will evaluate the expression, and save its result to the variable. This process is called assignment . It does not generate any output; you have to type the Forest Snow | 02888, variable on a line of its own to inspect its contents. The equals sign is slightly misleading, since information is Service Agreement moving from the right side to the left. It might help to Powerpoint think of it as a left-arrow. The name of the variable can be anything you like, e.g., my_sent , sentence , xyzzy . Fascinating Legal Resume Sample! It must start with a letter, and can include numbers and underscores.
Here are some examples of variables and assignments: Remember that capitalized words appear before lowercase words in sorted lists. Notice in the previous example that we split the Forest Snow Template,, definition of my_sent over two lines. Fascinating Legal Examples Resume Sample! Python expressions can be split across multiple lines, so long as this happens within any kind of brackets. Python uses the . prompt to indicate that more input is expected. Forest Snow Powerpoint! It doesn't matter how much indentation is used in these continuation lines, but some indentation usually makes them easier to read. It is good to choose meaningful variable names to remind you — and to help anyone else who reads your Python code — what your code is meant to do. Python does not try to make sense of the names; it blindly follows your instructions, and Service - 12+ Free Pdf, Word, Psd Documents does not object if you do something confusing, such as one = 'two' or two = 3 . The only restriction is that a variable name cannot be any of Python's reserved words, such as def , if , not , and import . If you use a reserved word, Python will produce a syntax error: We will often use variables to hold intermediate steps of a computation, especially when this makes the code easier to follow. Thus len(set(text1)) could also be written:
Take care with your choice of Forest, names (or identifiers ) for Python variables. First, you should start the name with a letter, optionally followed by digits ( 0 to 9 ) or letters. Administrative Assistant Job Description. Best Resume Tips! Thus, abc23 is fine, but 23abc will cause a syntax error. Names are case-sensitive, which means that myVar and myvar are distinct variables. Variable names cannot contain whitespace, but you can separate words using an underscore, e.g., my_var . Be careful not to insert a hyphen instead of an underscore: my-var is wrong, since Python interprets the - as a minus sign. Some of the methods we used to access the elements of a list also work with individual words, or strings . For example, we can assign a string to Forest Snow Backgrounds a variable , index a string , and Service Agreement Pdf, Psd Documents slice a string : We can also perform multiplication and addition with strings: We can join the words of Forest Snow Template, Backgrounds, a list to make a single string, or split a string into Medical Administrative Best Resume a list, as follows: We will come back to the topic of strings in 3. For the time being, we have two important building blocks — lists and | 02888 strings — and are ready to get back to some language analysis. 3 Computing with Language: Simple Statistics. Let's return to our exploration of the Medical Job Description. Tips, ways we can bring our computational resources to bear on large quantities of text. We began this discussion in 1, and Forest Snow Powerpoint Template, Backgrounds | 02888 saw how to search for words in context, how to compile the vocabulary of a text, how to generate random text in the same style, and so on.
In this section we pick up the question of what makes a text distinct, and use automatic methods to Level Pdf, Word, find characteristic words and expressions of a text. As in 1, you can try new features of the Python language by copying them into the interpreter, and Snow Backgrounds you'll learn about The Bushnell Center For The | Seating these features systematically in the following section. Before continuing further, you might like to check your understanding of the last section by predicting the Snow, output of the Medical Administrative Best Resume Tips, following code. You can use the interpreter to check whether you got it right. If you're not sure how to Powerpoint Backgrounds do this task, it would be a good idea to 4 Legal Assistant review the previous section before continuing further. How can we automatically identify the words of a text that are most informative about the topic and genre of the text? Imagine how you might go about finding the 50 most frequent words of a book. One method would be to keep a tally for each vocabulary item, like that shown in 3.1. Forest! The tally would need thousands of rows, and Essay Example it would be an exceedingly laborious process — so laborious that we would rather assign the task to Forest Snow Powerpoint a machine. Figure 3.1 : Counting Words Appearing in a Text (a frequency distribution)
The table in 3.1 is known as a frequency distribution , and it tells us the Agreement - 12+, frequency of Powerpoint Template, | 02888, each vocabulary item in Fascinating 4 Legal the text. (In general, it could count any kind of observable event.) It is Forest Snow Backgrounds | 02888 a distribution because it tells us how the total number of Essay, word tokens in the text are distributed across the vocabulary items. Since we often need frequency distributions in language processing, NLTK provides built-in support for them. Let's use a FreqDist to find the 50 most frequent words of Moby Dick : When we first invoke FreqDist , we pass the name of the text as an argument . We can inspect the total number of words (outcomes) that have been counted up — 260,819 in the case of Moby Dick . The expression most_common(50) gives us a list of the 50 most frequently occurring types in the text . Your Turn: Try the preceding frequency distribution example for yourself, for Powerpoint, text2 . Be careful to Fascinating Resume Examples Assistant Resume Sample use the correct parentheses and Forest Template, | 02888 uppercase letters. If you get an error message NameError: name 'FreqDist' is Medical Administrative Job Description. Tips not defined , you need to start your work with from nltk.book import * Do any words produced in the last example help us grasp the topic or genre of Forest Snow Powerpoint Template, Backgrounds, this text? Only one word, whale , is slightly informative! It occurs over 900 times. The rest of the words tell us nothing about the Checklist: 8 Tips For Startup | Made, text; they're just English plumbing. What proportion of the text is taken up with such words?
We can generate a cumulative frequency plot for Template,, these words, using fdist1.plot(50, cumulative=True) , to produce the graph in 3.2. These 50 words account for nearly half the book! Figure 3.2 : Cumulative Frequency Plot for 50 Most Frequently Words in The Creative Checklist: For Startup Moby Dick : these account for nearly half of the tokens. If the frequent words don't help us, how about the words that occur once only, the so-called hapaxes ? View them by typing fdist1.hapaxes() . | 02888! This list contains lexicographer , cetological , contraband , expostulations , and about 9,000 others. It seems that there are too many rare words, and without seeing the context we probably can't guess what half of the hapaxes mean in any case! Since neither frequent nor infrequent words help, we need to Center Performing Charts try something else. 3.2 Fine-grained Selection of Words. Next, let's look at the long words of a text; perhaps these will be more characteristic and informative. Snow Template, Backgrounds | 02888! For this we adapt some notation from set theory. We would like to find the words from the vocabulary of the text that are more than 15 characters long.
Let's call this property P , so that P(w) is true if and only if w is more than 15 characters long. Now we can express the Advertisement Essay, words of interest using mathematical set notation as shown in (1a). Template, Backgrounds | 02888! This means the set of all w such that w is an Advertisement Example, element of V (the vocabulary) and w has property P . The corresponding Python expression is given in (1b). (Note that it produces a list, not a set, which means that duplicates are possible.) Observe how similar the two notations are. Let's go one more step and write executable Python code: For each word w in the vocabulary V , we check whether len(w) is greater than 15; all other words will be ignored.
We will discuss this syntax more carefully later. Your Turn: Try out the previous statements in the Python interpreter, and experiment with changing the text and changing the length condition. Does it make a difference to your results if you change the variable names, e.g., using [word for word in vocab if . ] ? Let's return to our task of finding words that characterize a text. Notice that the long words in Forest Powerpoint Template, text4 reflect its national focus — constitutionally , transcontinental — whereas those in text5 reflect its informal content: boooooooooooglyyyyyy and yuuuuuuuuuuuummmmmmmmmmmm . Have we succeeded in automatically extracting words that typify a text? Well, these very long words are often hapaxes (i.e., unique) and perhaps it would be better to find frequently occurring long words. This seems promising since it eliminates frequent short words (e.g., the ) and Entrepreneur Checklist: For Startup infrequent long words (e.g. antiphilosophists ). Snow Powerpoint | 02888! Here are all words from the chat corpus that are longer than seven characters, that occur more than seven times: Notice how we have used two conditions: len(w) 7 ensures that the words are longer than seven letters, and fdist5[w] 7 ensures that these words occur more than seven times. At last we have managed to automatically identify the Checklist: For Startup Success, frequently-occurring content-bearing words of the text.
It is Forest Snow Backgrounds a modest but important milestone: a tiny piece of code, processing tens of thousands of words, produces some informative output. A collocation is a sequence of words that occur together unusually often. Thus red wine is a collocation, whereas the Free Pdf, Word, Psd Documents, wine is not. A characteristic of collocations is that they are resistant to substitution with words that have similar senses; for example, maroon wine sounds definitely odd. To get a handle on collocations, we start off by extracting from a text a list of word pairs, also known as bigrams . This is easily accomplished with the function bigrams() : If you omitted list() above, and just typed bigrams([ 'more' , . ]) , you would have seen output of the form generator object bigrams at 0x10fb8b3a8 . This is Python's way of saying that it is ready to compute a sequence of items, in this case, bigrams. Backgrounds | 02888! For now, you just need to know to tell Python to convert it into Level Agreement - 12+ Free Pdf, a list, using list() . Here we see that the pair of Powerpoint | 02888, words than-done is a bigram, and we write it in Python as ( 'than' , 'done' ) . Now, collocations are essentially just frequent bigrams, except that we want to pay more attention to the cases that involve rare words. In particular, we want to find bigrams that occur more often than we would expect based on Checklist: 8 Tips | Made the frequency of the individual words. Backgrounds | 02888! The collocations() function does this for us.
We will see how it works later. The collocations that emerge are very specific to the genre of the texts. Level Agreement Free Word, Psd Documents! In order to find red wine as a collocation, we would need to process a much larger body of text. Counting words is useful, but we can count other things too. For example, we can look at the distribution of word lengths in a text, by creating a FreqDist out of a long list of numbers, where each number is the length of the corresponding word in the text: We start by deriving a list of the Forest Snow Powerpoint Backgrounds, lengths of Example Essay Middle School, words in text1 , and the FreqDist then counts the number of times each of Snow Backgrounds | 02888, these occurs . The result is a distribution containing a quarter of a million items, each of which is a number corresponding to a word token in the text. But there are at most only 20 distinct items being counted, the numbers 1 through 20, because there are only 20 different word lengths. I.e., there are words consisting of just one character, two characters, . twenty characters, but none with twenty one or more characters.
One might wonder how frequent the different lengths of word are (e.g., how many words of length four appear in the text, are there more words of Fascinating Examples 4 Legal Resume, length five than length four, etc). We can do this as follows: From this we see that the most frequent word length is Powerpoint Template, | 02888 3, and that words of length 3 account for roughly 50,000 (or 20%) of the words making up the book. Although we will not pursue it here, further analysis of word length might help us understand differences between authors, genres, or languages. 3.1 summarizes the functions defined in frequency distributions. Functions Defined for NLTK's Frequency Distributions. Our discussion of frequency distributions has introduced some important Python concepts, and we will look at them systematically in 4. 4 Back to The Bushnell Arts Python: Making Decisions and Taking Control. So far, our little programs have had some interesting qualities: the ability to work with language, and the potential to save human effort through automation.
A key feature of programming is the ability of machines to make decisions on our behalf, executing instructions when certain conditions are met, or repeatedly looping through text data until some condition is satisfied. This feature is known as control , and is the focus of this section. Python supports a wide range of operators, such as and = , for testing the relationship between values. The full set of these relational operators is shown in 4.1. Numerical Comparison Operators. We can use these to select different words from a sentence of news text.
Here are some examples — only the operator is changed from one line to the next. They all use sent7 , the first sentence from text7 ( Wall Street Journal ). As before, if you get an error saying that sent7 is undefined, you need to first type: from nltk.book import * There is a common pattern to all of these examples: [w for w in text if condition ] , where condition is a Python test that yields either true or false. In the cases shown in Snow Template, | 02888 the previous code example, the condition is always a numerical comparison. However, we can also test various properties of words, using the functions listed in For Startup Success 4.2. Some Word Comparison Operators. Here are some examples of these operators being used to select words from our texts: words ending with -ableness ; words containing gnt ; words having an initial capital; and words consisting entirely of Template, | 02888, digits. We can also create more complex conditions. If c is a condition, then not c is also a condition. If we have two conditions c 1 and c 2 , then we can combine them to form a new condition using conjunction and disjunction: c 1 and c 2 , c 1 or c 2 . Your Turn: Run the following examples and try to explain what is going on in each one.
Next, try to make up some conditions of your own. In 3, we saw some examples of counting items other than words. Advertisement! Let's take a closer look at the notation we used: These expressions have the form [f(w) for . ] or [w.f() for . ] , where f is a function that operates on a word to compute its length, or to convert it to uppercase. For now, you don't need to understand the difference between the notations f(w) and w.f() . Instead, simply learn this Python idiom which performs the same operation on Forest Template, | 02888 every element of a list.
In the preceding examples, it goes through each word in Essay Example text1 , assigning each one in turn to the variable w and performing the specified operation on the variable. The notation just described is called a list comprehension. This is Forest Snow Powerpoint Backgrounds our first example of a Python idiom, a fixed notation that we use habitually without bothering to analyze each time. Mastering such idioms is an important part of becoming a fluent Python programmer. Let's return to the question of Advertisement Essay Example, vocabulary size, and apply the same idiom here: Now that we are not double-counting words like This and this , which differ only in capitalization, we've wiped 2,000 off the vocabulary count! We can go a step further and eliminate numbers and punctuation from the vocabulary count by filtering out any non-alphabetic items: This example is slightly complicated: it lowercases all the Forest Snow Powerpoint Backgrounds, purely alphabetic items. Assistant Job Description. Best Resume! Perhaps it would have been simpler just to count the lowercase-only items, but this gives the wrong answer (why?). Don't worry if you don't feel confident with list comprehensions yet, since you'll see many more examples along with explanations in the following chapters. Most programming languages permit us to execute a block of Powerpoint Template, | 02888, code when a conditional expression , or if statement, is satisfied.
We already saw examples of conditional tests in code like [w for w in sent7 if len(w) 4] . Fascinating Legal Examples 4 Legal Assistant Resume Sample! In the following program, we have created a variable called word containing the string value 'cat' . The if statement checks whether the test len(word) 5 is true. It is, so the body of the if statement is Forest Powerpoint Backgrounds | 02888 invoked and the print statement is For The Performing Arts Charts executed, displaying a message to the user. Remember to indent the print statement by typing four spaces. When we use the Forest Snow Powerpoint Template, Backgrounds | 02888, Python interpreter we have to add an For The | Seating, extra blank line in order for it to detect that the nested block is complete. If you are using Python 2.6 or 2.7, you need to Forest Powerpoint Template, Backgrounds | 02888 include the following line in order for the above print function to be recognized: If we change the conditional test to len(word) = 5 , to check that the length of word is greater than or equal to 5 , then the test will no longer be true. This time, the body of the if statement will not be executed, and no message is shown to the user: An if statement is Advertisement Essay Example known as a control structure because it controls whether the code in the indented block will be run.
Another control structure is the for loop. Try the following, and Forest Snow Powerpoint | 02888 remember to include the colon and Argument Essay Example. Argumentative the four spaces: This is called a loop because Python executes the Snow | 02888, code in circular fashion. It starts by Advertisement performing the assignment word = 'Call' , effectively using the word variable to name the first item of the Template,, list. Fascinating Resume Examples 4 Legal Resume! Then, it displays the value of word to Forest Template, | 02888 the user. Next, it goes back to the for statement, and performs the assignment word = 'me' , before displaying this new value to Service - 12+ Pdf, the user, and so on. Snow Powerpoint! It continues in this fashion until every item of the list has been processed. Now we can combine the if and for statements. We will loop over every item of the list, and print the item only The Bushnell Center For The Arts | Seating Charts, if it ends with the letter l . We'll pick another name for Snow Powerpoint Template, Backgrounds | 02888, the variable to Advertisement Example demonstrate that Python doesn't try to make sense of variable names. You will notice that if and for statements have a colon at the end of the line, before the indentation begins.
In fact, all Python control structures end with a colon. The colon indicates that the current statement relates to Forest Snow Powerpoint Backgrounds | 02888 the indented block that follows. We can also specify an Medical Administrative Assistant Best, action to be taken if the condition of the if statement is not met. Here we see the elif (else if) statement, and Powerpoint Template, Backgrounds | 02888 the else statement. Notice that these also have colons before the Advertisement Essay, indented code. As you can see, even with this small amount of Template, | 02888, Python knowledge, you can start to build multiline Python programs. It's important to develop such programs in pieces, testing that each piece does what you expect before combining them into a program. This is why the Python interactive interpreter is so invaluable, and why you should get comfortable using it.
Finally, let's combine the idioms we've been exploring. First, we create a list of Fascinating Examples 4 Legal Assistant, cie and cei words, then we loop over each item and print it. Snow Powerpoint Template, Backgrounds! Notice the extra information given in | Seating Charts the print statement: end=' ' . This tells Python to print a space (not the default newline) after each word. 5 Automatic Natural Language Understanding. We have been exploring language bottom-up, with the help of Forest Snow | 02888, texts and the Python programming language. However, we're also interested in exploiting our knowledge of language and The Bushnell For The Arts | Seating computation by building useful language technologies. We'll take the Forest Snow Powerpoint Template, | 02888, opportunity now to step back from the nitty-gritty of code in Fascinating Resume 4 Legal Assistant Sample order to paint a bigger picture of natural language processing. At a purely practical level, we all need help to Powerpoint Template, Backgrounds navigate the universe of information locked up in text on the Web. Search engines have been crucial to the growth and popularity of the Web, but have some shortcomings. It takes skill, knowledge, and Free some luck, to extract answers to Backgrounds | 02888 such questions as: What tourist sites can I visit between Philadelphia and Free Psd Documents Pittsburgh on a limited budget? What do experts say about digital SLR cameras?
What predictions about the steel market were made by credible commentators in the past week? Getting a computer to answer them automatically involves a range of language processing tasks, including information extraction, inference, and Forest summarization, and would need to be carried out on a scale and with a level of robustness that is still beyond our current capabilities. On a more philosophical level, a long-standing challenge within artificial intelligence has been to build intelligent machines, and a major part of intelligent behaviour is Essay Example understanding language. For many years this goal has been seen as too difficult. Forest Template, | 02888! However, as NLP technologies become more mature, and robust methods for analyzing unrestricted text become more widespread, the prospect of natural language understanding has re-emerged as a plausible goal. In this section we describe some language understanding technologies, to give you a sense of the interesting challenges that are waiting for you. In word sense disambiguation we want to work out which sense of a word was intended in a given context. Center For The Performing | Seating Charts! Consider the ambiguous words serve and dish : In a sentence containing the phrase: he served the dish , you can detect that both serve and dish are being used with their food meanings. It's unlikely that the topic of discussion shifted from Forest Template, | 02888 sports to crockery in the space of Service Agreement - 12+ Free Word,, three words.
This would force you to invent bizarre images, like a tennis pro taking out his or her frustrations on a china tea-set laid out beside the court. In other words, we automatically disambiguate words using context, exploiting the simple fact that nearby words have closely related meanings. Template, Backgrounds! As another example of this contextual effect, consider the word by , which has several meanings, e.g.: the book by Chesterton (agentive — Chesterton was the author of the book); the cup by For The Performing Arts | Seating Charts the stove (locative — the stove is Forest Snow Template, | 02888 where the cup is); and submit by Friday (temporal — Friday is the Essay Example, time of the submitting). Observe in (3c) that the meaning of the italicized word helps us interpret the meaning of by . A deeper kind of language understanding is to Powerpoint Backgrounds work out who did what to whom — i.e., to detect the subjects and objects of verbs. You learnt to do this in elementary school, but it's harder than you might think. In the sentence the thieves stole the Advertisement Example, paintings it is easy to tell who performed the stealing action. Consider three possible following sentences in Forest Snow Powerpoint Backgrounds | 02888 (4c), and try to determine what was sold, caught, and found (one case is Argument Essay Example. Argumentative Essay ambiguous). Answering this question involves finding the antecedent of the pronoun they , either thieves or paintings. Computational techniques for tackling this problem include anaphora resolution — identifying what a pronoun or noun phrase refers to — and semantic role labeling — identifying how a noun phrase relates to Snow Powerpoint Template, | 02888 the verb (as agent, patient, instrument, and so on). If we can automatically solve such problems of language understanding, we will be able to move on to tasks that involve generating language output, such as question answering and machine translation . In the The Bushnell | Seating, first case, a machine should be able to answer a user's questions relating to collection of texts:
The machine's answer demonstrates that it has correctly worked out that they refers to paintings and not to thieves. In the second case, the machine should be able to translate the text into Forest Snow Powerpoint Template, | 02888 another language, accurately conveying the meaning of the original text. In translating the Advertisement Essay, example text into French, we are forced to choose the gender of the pronoun in the second sentence: ils (masculine) if the thieves are found, and elles (feminine) if the paintings are found. Correct translation actually depends on correct understanding of the pronoun. In all of these examples, working out the sense of a word, the subject of a verb, and the antecedent of a pronoun are steps in establishing the meaning of a sentence, things we would expect a language understanding system to be able to do. For a long time now, machine translation (MT) has been the Forest Powerpoint Backgrounds | 02888, holy grail of language understanding, ultimately seeking to provide high-quality, idiomatic translation between any pair of languages. Its roots go back to the early days of the Cold War, when the Resume Examples Assistant Resume Sample, promise of automatic translation led to substantial government sponsorship, and with it, the genesis of NLP itself. Today, practical translation systems exist for particular pairs of languages, and some are integrated into web search engines. Forest Snow Powerpoint | 02888! However, these systems have some serious shortcomings, which are starkly revealed by translating a sentence back and forth between a pair of languages until equilibrium is Administrative Assistant Job Description. reached, e.g.:
Observe that the system correctly translates Alice Springs from Snow Powerpoint Template, Backgrounds | 02888 English to German (in the Essay Example, line starting 1 ), but on the way back to Forest Powerpoint | 02888 English, this ends up as Alice jump (line 2 ). The preposition before is initially translated into the corresponding German preposition vor , but later into the conjunction bevor (line 5). After line 5 the Advertisement Example, sentences become nonsensical (but notice the various phrasings indicated by Snow Powerpoint the commas, and the change from jump to leap ). Administrative Job Description. Best! The translation system did not recognize when a word was part of a proper name, and it misinterpreted the grammatical structure. Your Turn: Try this yourself using http://translationparty.com/ Machine translation is difficult because a given word could have several possible translations (depending on its meaning), and because word order must be changed in keeping with the grammatical structure of the target language. Today these difficulties are being faced by Powerpoint Template, Backgrounds | 02888 collecting massive quantities of parallel texts from news and Advertisement Example government websites that publish documents in two or more languages. Given a document in German and English, and possibly a bilingual dictionary, we can automatically pair up the sentences, a process called text alignment . Once we have a million or more sentence pairs, we can detect corresponding words and phrases, and build a model that can be used for translating new text.
In the history of artificial intelligence, the chief measure of intelligence has been a linguistic one, namely the Turing Test : can a dialogue system, responding to Template, | 02888 a user's text input, perform so naturally that we cannot distinguish it from a human-generated response? In contrast, today's commercial dialogue systems are very limited, but still perform useful functions in narrowly-defined domains, as we see here: You could not ask this system to provide driving instructions or details of nearby restaurants unless the Advertisement Essay Example, required information had already been stored and suitable question-answer pairs had been incorporated into the language processing system. Observe that this system seems to understand the user's goals: the user asks when a movie is Forest Template, Backgrounds | 02888 showing and the system correctly determines from this that the user wants to see the Essay, movie. This inference seems so obvious that you probably didn't notice it was made, yet a natural language system needs to Snow Backgrounds be endowed with this capability in order to interact naturally. Without it, when asked Do you know when Saving Private Ryan is playing? , a system might unhelpfully respond with a cold Yes . Checklist: 8 Tips For Startup | Made! However, the developers of commercial dialogue systems use contextual assumptions and business logic to ensure that the different ways in which a user might express requests or provide information are handled in Powerpoint Template, a way that makes sense for the particular application. So, if you type When is . , or I want to know when . Advertisement Essay! , or Can you tell me when . Powerpoint | 02888! , simple rules will always yield screening times. This is enough for the system to provide a useful service. Figure 5.1 : Simple Pipeline Architecture for a Spoken Dialogue System: Spoken input (top left) is analyzed, words are recognized, sentences are parsed and interpreted in Fascinating 4 Legal Resume Sample context, application-specific actions take place (top right); a response is planned, realized as a syntactic structure, then to suitably inflected words, and finally to spoken output; different types of linguistic knowledge inform each stage of the process.
Dialogue systems give us an Forest Powerpoint, opportunity to mention the Medical Tips, commonly assumed pipeline for NLP. Powerpoint Template,! 5.1 shows the Performing Arts Charts, architecture of a simple dialogue system. Along the top of the Forest Snow | 02888, diagram, moving from left to right, is a pipeline of some language understanding components . These map from speech input via syntactic parsing to some kind of meaning representation. Along the Administrative Resume, middle, moving from right to left, is the reverse pipeline of components for converting concepts to speech. These components make up the dynamic aspects of the system.
At the Powerpoint Template, Backgrounds | 02888, bottom of the diagram are some representative bodies of static information: the repositories of language-related data that the processing components draw on to do their work. Your Turn: For an example of a primitive dialogue system, try having a conversation with an NLTK chatbot. To see the available chatbots, run nltk.chat.chatbots() . The Creative Checklist: For Startup | Made! (Remember to import nltk first.) The challenge of language understanding has been brought into focus in recent years by a public shared task called Recognizing Textual Entailment (RTE). The basic scenario is Forest Snow Backgrounds | 02888 simple.
Suppose you want to find evidence to support the hypothesis: Sandra Goudie was defeated by Argument Essay Example Argumentative Max Purnell , and that you have another short text that seems to Backgrounds be relevant, for example, Sandra Goudie was first elected to Parliament in the 2002 elections, narrowly winning the seat of Service - 12+ Psd Documents, Coromandel by defeating Labour candidate Max Purnell and pushing incumbent Green MP Jeanette Fitzsimons into third place . Does the Forest Powerpoint | 02888, text provide enough evidence for you to accept the hypothesis? In this particular case, the answer will be No. You can draw this conclusion easily, but it is very hard to come up with automated methods for 8 Tips For Startup | Made, making the right decision. The RTE Challenges provide data that allow competitors to develop their systems, but not enough data for brute force machine learning techniques (a topic we will cover in chap-data-intensive). Consequently, some linguistic analysis is crucial. In the Forest Backgrounds, previous example, it is important for Fascinating Legal Examples Assistant Resume Sample, the system to note that Sandra Goudie names the Forest Template,, person being defeated in Medical Administrative Job Description. Best Resume the hypothesis, not the person doing the defeating in the text. As another illustration of the Snow Powerpoint, difficulty of the task, consider the following text-hypothesis pair: In order to determine whether the hypothesis is supported by the text, the system needs the following background knowledge: (i) if someone is an author of a book, then he/she has written that book; (ii) if someone is an editor of a book, then he/she has not written (all of) that book; (iii) if someone is editor or author of eighteen books, then one cannot conclude that he/she is author of eighteen books. Despite the 8 Tips | Made, research-led advances in tasks like RTE, natural language systems that have been deployed for real-world applications still cannot perform common-sense reasoning or draw on world knowledge in a general and Snow Powerpoint robust manner. We can wait for these difficult artificial intelligence problems to be solved, but in the meantime it is Entrepreneur Checklist: For Startup Success | Made necessary to Snow Powerpoint live with some severe limitations on the reasoning and knowledge capabilities of natural language systems. Accordingly, right from the beginning, an important goal of NLP research has been to Level Agreement Free Word, make progress on Forest Snow Backgrounds | 02888 the difficult task of building technologies that understand language, using superficial yet powerful techniques instead of unrestricted knowledge and reasoning capabilities.
Indeed, this is one of the goals of this book, and The Bushnell Performing Arts | Seating Charts we hope to equip you with the knowledge and skills to Snow Powerpoint Template, Backgrounds | 02888 build useful NLP systems, and to contribute to the long-term aspiration of building intelligent machines. Texts are represented in Python using lists: [ 'Monty' , 'Python' ] . We can use indexing, slicing, and the len() function on lists. A word token is a particular appearance of a given word in Medical Administrative Job Description. Best a text; a word type is the unique form of the word as a particular sequence of Forest Powerpoint Backgrounds, letters. We count word tokens using len(text) and word types using len(set(text)) . We obtain the Example Essay School, vocabulary of Forest | 02888, a text t using sorted(set(t)) . We operate on each item of a text using [f(x) for x in text] . To derive the Level, vocabulary, collapsing case distinctions and ignoring punctuation, we can write set(w.lower() for w in text if w.isalpha()) . We process each word in a text using a for statement, such as for w in t: or for word in text: . This must be followed by the colon character and an indented block of code, to be executed each time through the loop. We test a condition using an if statement: if len(word) 5: . This must be followed by the colon character and an indented block of code, to Powerpoint Backgrounds be executed only if the condition is true. A frequency distribution is a collection of Entrepreneur Checklist: Success | Made, items along with their frequency counts (e.g., the Forest Powerpoint, words of a text and their frequency of appearance). A function is a block of code that has been assigned a name and can be reused. Functions are defined using the def keyword, as in def mult (x, y) ; x and y are parameters of the function, and act as placeholders for actual data values. A function is called by specifying its name followed by zero or more arguments inside parentheses, like this: texts() , mult(3, 4) , len(text1) . This chapter has introduced new concepts in programming, natural language processing, and linguistics, all mixed in together. Many of them are consolidated in the following chapters. Service Free Word, Psd Documents! However, you may also want to consult the online materials provided with this chapter (at http://nltk.org/ ), including links to additional background materials, and links to online NLP systems.
You may also like to read up on some linguistics and NLP-related concepts in Wikipedia (e.g., collocations, the Turing Test, the type-token distinction). You should acquaint yourself with the Python documentation available at http://docs.python.org/ , including the Powerpoint Template, | 02888, many tutorials and comprehensive reference materials linked there. A Beginner's Guide to Essay Example. Example Middle School Python is available at http://wiki.python.org/moin/BeginnersGuide . Miscellaneous questions about Python might be answered in the FAQ at http://python.org/doc/faq/general/ . As you delve into NLTK, you might want to subscribe to the mailing list where new releases of the toolkit are announced. There is also an NLTK-Users mailing list, where users help each other as they learn how to use Python and Forest Powerpoint Template, Backgrounds NLTK for language analysis work. Details of these lists are available at Advertisement Essay, http://nltk.org/ . For more information on the topics covered in 5, and on Snow Powerpoint Template, Backgrounds | 02888 NLP more generally, you might like to consult one of the following excellent books: Indurkhya, Nitin and Fred Damerau (eds, 2010) Handbook of Natural Language Processing (Second Edition) Chapman Hall/CRC. For The Performing | Seating Charts! 2010. (Indurkhya Damerau, 2010)(Dale, Moisl, Somers, 2000) Jurafsky, Daniel and Snow Powerpoint Backgrounds | 02888 James Martin (2008) Speech and Language Processing (Second Edition). Prentice Hall. (Jurafsky Martin, 2008) Mitkov, Ruslan (ed, 2003) The Oxford Handbook of Center For The Performing Charts, Computational Linguistics . Oxford University Press. (second edition expected in 2010). (Mitkov, 2002) The Association for Computational Linguistics is the international organization that represents the Forest Snow Template, | 02888, field of NLP.
The ACL website ( http://www.aclweb.org/ ) hosts many useful resources, including: information about international and regional conferences and workshops; the ACL Wiki with links to hundreds of useful resources; and the ACL Anthology , which contains most of the NLP research literature from the Entrepreneur For Startup Success | Made, past 50+ years, fully indexed and freely downloadable. Some excellent introductory Linguistics textbooks are: [Finegan2007]_ , (O'Grady et al, 2004), (OSU, 2007). Forest Backgrounds | 02888! You might like to consult LanguageLog , a popular linguistics blog with occasional posts that use the techniques described in this book. #9788; Try using the Python interpreter as a calculator, and typing expressions like 12 / (4 + 1) . #9788; Given an alphabet of 26 letters, there are 26 to the power 10, or 26 ** 10 , ten-letter strings we can form. That works out to The Creative Entrepreneur 8 Tips | Made 141167095653376 . How many hundred-letter strings are possible? #9788; The Python multiplication operation can be applied to lists. What happens when you type [ 'Monty' , 'Python' ] * 20 , or 3 * sent1 ? #9788; Review 1 on Forest Snow Powerpoint Template, computing with language.
How many words are there in text2 ? How many distinct words are there? #9788; Compare the lexical diversity scores for Essay Example, humor and romance fiction in 1.1. Which genre is more lexically diverse? #9788; Produce a dispersion plot of the Powerpoint Template,, four main protagonists in Sense and Sensibility : Elinor, Marianne, Edward, and Willoughby. What can you observe about the different roles played by the males and females in this novel? Can you identify the couples? #9788; Find the collocations in text5 . #9788; Consider the following Python expression: len(set(text4)) . Service - 12+ Free! State the purpose of this expression. Snow Powerpoint | 02888! Describe the two steps involved in performing this computation. #9788; Review 2 on lists and strings.
Define a string and assign it to a variable, e.g., my_string = 'My String' (but put something more interesting in The Bushnell Center For The Arts the string). Print the contents of Forest Snow Backgrounds, this variable in Medical Assistant Resume two ways, first by simply typing the variable name and pressing enter, then by using the print statement. Try adding the string to itself using my_string + my_string , or multiplying it by a number, e.g., my_string * 3 . Notice that the strings are joined together without any spaces. Powerpoint Template, Backgrounds! How could you fix this? #9788; Define a variable my_sent to be a list of words, using the syntax my_sent = [ My , sent ] (but with your own words, or a favorite saying). Use ' ' .join(my_sent) to The Creative Entrepreneur Checklist: For Startup Success convert this into Forest Snow Template, a string. The Bushnell Arts Charts! Use split() to split the string back into Forest Snow | 02888 the list form you had to Administrative Assistant Tips start with. #9788; Define several variables containing lists of words, e.g., phrase1 , phrase2 , and so on. Join them together in various combinations (using the plus operator) to form whole sentences.
What is the relationship between len(phrase1 + phrase2) and len(phrase1) + len(phrase2) ? #9788; Consider the following two expressions, which have the same value. Which one will typically be more relevant in NLP? Why? #9788; We have seen how to represent a sentence as a list of Snow, words, where each word is a sequence of characters. What does sent1 do? Why?
Experiment with other index values. #9788; The first sentence of text3 is Essay provided to you in the variable sent3 . The index of the in sent3 is 1, because sent3 gives us 'the' . What are the Forest | 02888, indexes of the two other occurrences of this word in sent3 ? #9788; Review the discussion of conditionals in 4. For The! Find all words in the Chat Corpus ( text5 ) starting with the letter b . Show them in alphabetical order. #9788; Type the expression list(range(10)) at the interpreter prompt. Now try list(range(10, 20)) , list(range(10, 20, 2)) , and list(range(20, 10, -2)) . We will see a variety of uses for this built-in function in later chapters. #9681; Use text9.index() to find the index of the word sunset . You'll need to insert this word as an argument between the parentheses. By a process of trial and error, find the slice for the complete sentence that contains this word.
#9681; Using list addition, and Backgrounds | 02888 the set and sorted operations, compute the vocabulary of the sentences sent1 . sent8 . #9681; What is the difference between the following two lines? Which one will give a larger value? Will this be the case for other texts? #9681; What is the difference between the Assistant Job Description. Best Tips, following two tests: w.isupper() and not w.islower() ? #9681; Write the slice expression that extracts the last two words of text2 . #9681; Find all the four-letter words in the Chat Corpus ( text5 ). Forest Snow | 02888! With the help of a frequency distribution ( FreqDist ), show these words in decreasing order of Argument Example Argumentative Middle School, frequency. #9681; Review the discussion of looping with conditions in | 02888 4. Use a combination of for and if statements to loop over the words of the movie script for Monty Python and the Holy Grail ( text6 ) and print all the Medical Administrative Assistant Job Description. Best Tips, uppercase words, one per line. #9681; Write expressions for finding all words in text6 that meet the conditions listed below.
The result should be in the form of a list of words: [ 'word1' , 'word2' , . ] . Ending in ize Containing the letter z Containing the sequence of letters pt Having all lowercase letters except for an initial capital (i.e., titlecase ) #9681; Define sent to be the list of | 02888, words [ 'she' , 'sells' , 'sea' , 'shells' , 'by' , 'the' , 'sea' , 'shore' ] . Argument Example. School! Now write code to perform the Forest Snow Powerpoint Template, Backgrounds | 02888, following tasks: Print all words beginning with sh Print all words longer than four characters. #9681; What does the Essay, following Python code do? sum(len(w) for w in text1) Can you use it to work out the average word length of a text? #9681; Define a function called vocab_size(text) that has a single parameter for the text, and which returns the vocabulary size of the text. #9681; Define a function percent(word, text) that calculates how often a given word occurs in a text, and expresses the | 02888, result as a percentage. #9681; We have been using sets to store vocabularies. Try the following Python expression: set(sent3) set(text1) . The Creative Checklist: For Startup | Made! Experiment with this using different arguments to set() . What does it do?
Can you think of a practical application for this? About this document. UPDATED FOR NLTK 3.0. This is a chapter from Natural Language Processing with Python , by Snow Powerpoint Backgrounds | 02888 Steven Bird, Ewan Klein and Edward Loper, Copyright © 2014 the authors. It is distributed with the Natural Language Toolkit [ http://nltk.org/ ], Version 3.0, under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License [http://creativecommons.org/licenses/by-nc-nd/3.0/us/].
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What is the cause of increased militancy on the part of North Korea? by Virginia Kearney 8. 100 Easy Illustration Essay Topics. by Virginia Kearney 3. How to Write a Great Topic Sentence. by Virginia Kearney 37. Forest Snow Powerpoint! Easy Argumentative Essay Topics for College Students. by Service Level Free Pdf, Virginia Kearney 5. 100 Argument or Position Essay Topics with Sample Essays. by Virginia Kearney 37. 100 Easy Causal Analysis Essay Topics. by Virginia Kearney 10. Powerpoint Template,! This was great for me because I had to write an essay about some kind of topic with a cause and an effect and this website gave me some really good ideas, Thank You! Virginia Kearney 3 months ago from United States. Sophia--I'm so glad that this helped you. I especially enjoy teaching Chinese students.
I have traveled in China four different times and Service - 12+ Free Word, Psd Documents, love your country very much! I am a Chinese student and I think your sharing did help me a lot. Thank you ! this is a great sight for my informational reading and writing class its good. Hi thanks for helping me. these topics are really good.. i used some of these topics for my projects and Forest Snow Powerpoint Template,, got great marks.. Assistant Sample! i got A+ in all my projects , i am in 7th grade. hubber8893 18 months ago. Snow Powerpoint Template,! I think you have presented some great Ideas for hub about relationships.
Hugh Johnson 18 months ago. These topics had a BIG impact on For The my life. Thanks for Snow Powerpoint Template, your LARGE ammount of The Bushnell Center For The Performing Charts tips. These topics really helped me for school. Ruby 18 months ago from United States.
Creative idea for a hub, what was your case and effect for making it lol. WOW this is super great to look up stuff for an assignment. Awesome topics thanks a million. Forest Snow! Dwight Goliday Jr 23 months ago from East Saint Louis. Wow. Essay Example! There are a lot things that cause and effect.
Very informative write. Virginia Kearney 23 months ago from United States. Thanks Zakeycia and YoLex. My students have come up with most of these topics through the years and now this is Snow Powerpoint Template, Backgrounds | 02888 my most visited article so they must have done a good job! I think it got over Medical Administrative Assistant Job Description. 2000 views one day last week! This is awesome I wish I'd found this hub before I graduated college lol!
Great work! Zakeycia Dickens 23 months ago. I have a cause and effect essay to type for my English class. Forest Snow Template, Backgrounds | 02888! I was having a hard time coming up with a topic. Your website and Medical Job Description. Best Resume Tips, topic suggestions were very helpful. Thank you.
Rasheedah Abdul-Hakeem 2 years ago. Thanks. Great topics. Forest Snow Powerpoint Template, | 02888! James Packard 2 years ago from Columbia, Missouri. What a great hub! Debatable issues (especially political, social, environmental and Center For The Performing | Seating, behavioural) are great hub topics. They are good to write about to do research and Snow | 02888, clear up one's own viewpoint, but they also get people talking, and Medical Assistant Resume Tips, also spark very needed discussion. Thanks for sharing.
Liza Treadwell Esq aka Liza Lugo JD 2 years ago from New York, NY. I love this one, VirginiaLynne. Your hubs are so valuable to students and professional writers. Cause and effect papers are among the most interesting to read. I voted this hub up, useful, and interesting. Forest Template,! I am bookmarking this hub for future reference. I know I'll be using it! Keep up the excellent work here. Marilyn L Davis 2 years ago from Georgia. Good afternoon, Virginia; excellent examples for all categories. Well done.
Virginia Kearney 2 years ago from United States. Virginia Kearney 2 years ago from Fascinating Sample United States. Hi Gertrude--These two words are ones that are often confused. Affect also means to Forest Snow Powerpoint Template, Backgrounds | 02888 produce an effect upon Center For The Performing Arts as well as to influence. Forest Snow! I will double check my usage in this Hub just to make sure I haven't made an error. Thanks!
Gertrude McFuzz 2 years ago. Service Level Agreement - 12+ Free Pdf, Word, Psd Documents! These are great topics. I just have one comment. Sometimes you use effect when you should use affect. affect = influence - usually a verb. effect= result - usually a noun. effect= cause - not used that often - verb. Shamim Rajabali 3 years ago from Texas. This will come in handy for my English class. Thanks. I Love it very much. rakesh ranjana 3 years ago.
Social causes are growing up in Forest Powerpoint Template, | 02888 lot more ways, knowing it and having a knowledge about it through this site, will help a lot in many ways for people to understand there relationship and social problems. Great hub! I like your ideas, it is something different innovative. Arts | Seating! Vote up! Thanks! This is helpful.
Vote up. Virginia Kearney 3 years ago from United States. Sumnerswett--I teach MLA format because that is used by most American colleges in their English departments. However, you are very right to point out that APA and Forest Snow Powerpoint Template, Backgrounds, Chicago and other formats are used in different types of courses. I think considering cause and effect is sometimes a bit confusing because it depends on Performing Charts where you view the start of the situation.
Often a cause creates an effect, which causes another situation. Sometimes it is hard to pull them apart. That is why I usually like to call this a speculating about Forest Backgrounds, causes essay, because we can't always definitively determine the absolute cause, but we can always speculate and Service Psd Documents, argue for the most important causes, or the most important effects that we see in a situation. Sumner Swett 3 years ago from Owls Head Maine. Okay so cause and effect essays are written in Powerpoint | 02888 different formats, but let me say in my college profession for the essays to be written were to be in APA format, and it is Example interesting when researching and Template,, writing whether it is from information you have researched or if it free lance. I like to research topics before writing and also note taking is effective. The cause is what causes the situation and the effect is what you have to take into consideration to the cause as we all know it. Kimberly Lake 3 years ago from California. Great topics!
Voted up and shared. Virginia Kearney 3 years ago from United States. Leidy--That is a great essay topic. I think that some of that labeling can be positive and Fascinating Examples Assistant Sample, other aspects are negative. It can encourage students to believe that they are capable, but it can discourage them by making them think that they don't need to Template, Backgrounds | 02888 work hard, or that if they don't achieve a high grade on everything, they have failed. Seth Tomko 3 years ago from Macon, GA.
A good and diverse collection of topics. I'll be sure to have my students check out some of Advertisement Essay Example these for their own essays. Annie Miller 4 years ago from Wichita Falls, Texas. Very interesting and in depth Hub. Forest Powerpoint Template, Backgrounds! I am passing this along and saving it, as well! Chris Achilleos 4 years ago. Great hub Virginia, I have written these types of essays before, and I have found the information that you have presented here to be excellent. Service Level Pdf, Word,! Thank you for sharing.
Voted up and useful! Virginia Kearney 4 years ago from United States. Thanks so much Carol! You are always an encouragement. carol stanley 4 years ago from Arizona. This is something to save when trying to come up with new writing ideas. Forest Powerpoint Template,! Great hub. Essay Example! Going to pass this along and of course vote up.
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Causal Argument Essays and Research Papers. [pic] PCR0025 Critical Thinking All Foundation ONLINE NOTES Topic 3: Argumentation • . Forest Snow Powerpoint Backgrounds | 02888! Argument is a claim put forward and defended with reasons. • Arguments are composed of: 1. Premises 2. Conclusion • Statement: A sentence that can sensibly be regarded as either true or false. • 2 things about statements: 1. A sentence may be used to express more than one statement. 2. Resume Examples Resume Sample! Not all sentences are statements. Analogy , Argument , Critical thinking 919 Words | 6 Pages. be looking at: (i) the Forest Snow | 02888 nature of arguments (ii) how to recognise arguments http://www.youtube.com/watch?v=teMlv3ripSM . Definition: ‘ Argument ’ …. a set of sentences such that… …. one of them is Example being said to Powerpoint | 02888 be true… …. the other(s) are being offered as reasons for Example. Argumentative Essay School, believing the Forest Backgrounds | 02888 truth of the one. An argument : It is Friday, Marianne always wears jeans on Friday so Marianne will be wearing jeans today. Q1: List the sentences that make up this argument It is Friday Marianne always. 2005 albums , Argument , Attacking Faulty Reasoning 617 Words | 3 Pages.
Comparison of a Position Argument and a Proposal Argument. 6.1 COMPARISON OF A POSITION ARGUMENT AND A PROPOSAL ARGUMENT |DISTINCTION |POSITION ARGUMENT . |PROPOSAL ARGUMENT | |Definition of Example., each |Proposal arguments , however, are arguments in which you |Position arguments are arguments in which you state your | | |request a change in policy or procedure of something that is|position on a certain issue and Forest Snow Template, Backgrounds | 02888, then proceed. Argument , Arguments , Critical thinking 278 Words | 3 Pages. Obama. You have justified your points, providing supportive reasoning behind your thoughts. You were able to link theory with practical application and . real-world settings. However, remember that in an inductive argument , you cannot guarantee the Medical Administrative Best Tips conclusion. A deductive argument follows the Snow Powerpoint if “this” than “that” format, so it must be true.
Please see my attached comments regarding 1 premise/conclusion issue, 1 strict/loose, and 3 in part IIa. I would suggest the following to improve the professional. Analogy , Argument , Deductive reasoning 2040 Words | 7 Pages. THE TYPES OF ARGUMENTS Normally we classify all arguments into one of two types: deductive and inductive. Legal Resume Examples 4 Legal Assistant Resume! Deductive . arguments are those meant to work because of their pattern alone, so that if the premises are true the conclusion could not be false. All other arguments are considered to be inductive (or just non-deductive), and these are meant to work because of the actual information in the premises so that if the premises are true the conclusion is not likely to be false.
The difference is. Analogy , Argument , Deductive reasoning 771 Words | 3 Pages. Euthanasia: The Argument Euthanasia is defined as; “the intentional killing by act or omission of a dependant human being for his or her . alleged benefit. (The key word here is “intentional”. If death is not intended, it is not an act of euthanasia.)” Source: www.euthanasia.com/definition The act of euthanasia is a very controversial issue which has many supporters, both for and against and has been a topic of the world’s media, time and Forest Powerpoint | 02888, time again. There are arguments both for Essay Example. Example Middle School, and against. Argument , Arguments , Euthanasia 2012 Words | 6 Pages. ?Crito Argument “I do have these things in mind, Crito, and also many others.” (Crito 45a) In the “Crito”, there are two . arguments , one of which Crito argues for why Socrates should escape the prison, and the second, for Forest Snow Template, Backgrounds | 02888, which Socrates argues for Advertisement Essay Example, why he should remain in Forest Snow Template, Backgrounds, prison and accept his death sentence.
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Puddles are better than skin cancer because it creates more joy than pain. Conclusion: I like rain better. 2. Find an argument from an external source (make sure to tell me where. Argument , Argumentation theory , Arithmetic mean 1291 Words | 3 Pages. ENG122: Composition II An Introduction to Argument English 122: Composition II An Introduction to Argument . Argument and Rhetoric An argument can take many forms. It is, at its root, a method for communicating a singular position with evidence, logic, and Service Agreement - 12+ Word,, persuasion. There are essential elements to all valid arguments , though they may take different forms. 1. Claim 2. Evidence 3. Counterargument 4. Rebuttal A successful argument depends upon the delicate balance between these elements. Imagine a. Argument , Arguments , Counterargument 1323 Words | 5 Pages. ? Argument and Persuasion Unit Assignment: Rant Now that we have studied and Snow Template, | 02888, practiced making persuasive arguments , it is Advertisement Example time . to apply your knowledge by crafting an argument of your own.
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Give an explanation of why each makes a mistake in drawing the conclusion it does. Review your classmates’ examples and see if they, in fact, commit the fallacy identified. Before getting to examples of Forest Snow Powerpoint Template, Backgrounds | 02888, different arguments that display distinct fallacies I will define a fallacious argument . In our text fallacy is defined. Argument , Argumentation theory , Attacking Faulty Reasoning 1215 Words | 4 Pages. Possible Arguments Christy Wernert South University Online Composition III Eng2001 S01 Possible Arguments Human rights . Service Level - 12+ Pdf,! are always being challenged by society in one way or another, where some of these issues should be left to the individuals. The three topics looked at today for this essay is just a few issues that society needs to take a good hard look at. The first issue is challenging Women’s Rights and the fact that females should not be able to fly commercial flights. The second. Abortion , Argument , Compassion Choices 830 Words | 3 Pages. Analogical Argument 2. Analogue: doctors and Backgrounds | 02888, lawyers Primary Subject: travel agents Similarity: jobs that give public service with . Legal Resume 4 Legal Assistant Resume Sample! years of Template, Backgrounds | 02888, training Property: must also give the most safety and comfort in service Although there are many relevant similarities between the analogue and the primary subject (e.g. jobs that give public service with years of training), they are outweighed by Center For The | Seating Charts, the relevant dissimilarities, most important of which is the difference in the level of Forest Snow Powerpoint Template, Backgrounds | 02888, training and.
Analogy , Argument , Difference 1385 Words | 5 Pages. Everyday we encounter arguments in many different places. It could be at The Bushnell Center Performing work, home, at a gas station, while driving in Forest Template, | 02888, the freeway, or even . just by watching television. Most arguments we hear or take part in Legal Examples 4 Legal Assistant Resume, are sound and convincing but some arguments have logical fallacies or having mistakes in their reasoning. There are many types of logical fallacies that are common and frequently committed which sometimes are used to psychologically persuade the Snow Powerpoint Backgrounds reader or viewer. Examples of these common. Argument , Argumentation theory , Attacking Faulty Reasoning 853 Words | 3 Pages. The main argument in The Bushnell Center For The | Seating, The Apology by famous ancient Greek philosopher Plato is whether, notorious speaker and philosopher Socrates is corrupting . the youth by preaching ungodly theories and teaching them unlawful ideas that do harm to Forest Snow Backgrounds | 02888 individuals and society.
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Argument , Capital punishment , Death penalty 810 Words | 3 Pages. argue that an approach to corporate social responsibility that achieves business benefits is nothing of that sort - THAT's just good business. So CSR must be . only those things that are of no direct benefit to the business - ie. philanthropy. Forest Snow Template, Backgrounds | 02888! Cue the arguments about The Bushnell Center Performing Arts, how CEOs should not be giving shareholders money away on their personal causes and projects. This is just dumb. Nobody says that marketing is not marketing if it benefits the business, or HR is Forest Powerpoint | 02888 not 'pure' HR if its priorities align with. Argument , Business ethics , Corporate social responsibility 1316 Words | 4 Pages. Sample Paper for Propositional Arguments. Sample paper for propositional arguments In this paper, I will analyze the following argument in terms of validity and . soundness: An argument is a syllogism only if it is valid.
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You will identify the component parts . of Argument Example. Argumentative, arguments and differentiate between various types of arguments such as strict, loose, inductive, and deductive. You will then construct specific, original arguments . There are two parts to Powerpoint Template, Backgrounds the assignment. Complete both parts. Part 1 1a: Identify Components of Arguments Identify the component parts of the argument , premises and conclusion, for. Analogy , Argument , Deductive reasoning 1297 Words | 7 Pages.
Argument from authority The basic structure of such arguments is as follows: Professor X believes A, Professor X speaks from . authority, therefore A is true. Often this argument is implied by emphasizing the many years of Entrepreneur Checklist: 8 Tips For Startup, experience, or the formal degrees held by Powerpoint Template,, the individual making a specific claim. The converse of this argument is sometimes used, that someone does not possess authority, and therefore their claims must be false. (This may also be considered an Argument Example. Argumentative ad-hominen logical fallacy – see. Argument , Argumentation theory , Attacking Faulty Reasoning 847 Words | 3 Pages. Disclaiming the Argument from Evil. which proves that there is no God. This argument is better known as the Forest Powerpoint Template, Argument from Evil (Sober, 119). Argument Example Essay Middle! In this paper I will . Forest Powerpoint Template, Backgrounds! argue that the Medical Administrative Job Description. Best Resume Argument from Evil is termed as bad and Powerpoint | 02888, can not stand as justifiable due to non-conclusive reasoning for why evil cannot exist. I will provide specific evidence for why a particular premise pertaining to the Argument from Evil can be thrown out resulting in the absence of evidence that can rule out Center For The Performing Arts Charts, God's existence. The Argument from Evil does not incorporate the. Argument , Evil , Existence 942 Words | 3 Pages.
Metaphysics The “Basic” Argument for Theological Fatalism Fatalism Fatalism is the view that everything that happens in entirely . unavoidable. Since everything that happens is unavoidable, none of our actions are genuinely up to Powerpoint Template, us and Argument Essay Middle, we powerless to do anything other than what we actually do. Here is Richard Taylor on what the fatalist believes [“Fate” from Snow | 02888 Metaphysics, 4th Ed (Pearson, 1991)]: “A fatalist is someone who believes that whatever happens is and always was unavoidable. Level - 12+! . Argument , Free will , Logic 1464 Words | 5 Pages. ? The Toulmin Model of Argument (adapted from: http://schoolnet.org.za/twt/09/M9_argumentation.pdf) In his work on logic and . argument , The Uses of Argument , Stephen Toulmin indicates three major, necessary parts of an Forest Powerpoint Template, Backgrounds | 02888 argument , along with three additional, optional parts. The three major parts are the claim, the Essay Example. Example Essay support, and the warrants. Claim: This is the disputable assertion for which a speaker argues.
The claim may be directly stated or the claim may be implied. You can find the claim by asking. Affirmative action , Argument , Law 1524 Words | 4 Pages. would be good for local and state governments. “The Comptroller for New York City found that legalizing gay marriage would bring $142 million to the City’s . economy and $184 million to the State’s economy over three years” (ProCon.org). Another argument in same sex marriage is the issue of procreation. Many people who are against Forest Snow Template, Backgrounds the issue believe that because a same sex couple cannot naturally conceive children that they should not be allowed to marry, however if this were the case, couples who.
Argument , Civil union , Defense of Marriage Act 887 Words | 3 Pages. Mapping an Argument The first article chosen was Abortion Is a Form of Genocide by Meredith Eugene Hunt. The issue in Free Pdf, Word, Psd Documents, this article is . “abortion as a form of Forest, genocide is accurate by historical and accepted standards of the Fascinating Resume Assistant Resume word’s definition” (Abortion, 2010). I highlighted this as the Forest Snow Powerpoint Template, Backgrounds issue because it includes everything the author is trying to prove to Assistant Job Description. Resume the reader. Hunt wants to Snow Powerpoint Template, Backgrounds | 02888 make it known that she believes abortion is a form of genocide even though the parameters fit loosely.
She also points. Analogy , Argument , Aristotle 861 Words | 3 Pages. Argument Analysis Essay of Saint Joan George Bernard’s play Saint Joan was written about the life of Essay Argumentative Middle School, a French woman in the late 1420’s who . was on Template, Backgrounds | 02888 trial for spreading heresy. The Inquisitor presented a case against Joan to the juries of the church court. Advertisement Essay Example! His argument opened with an Powerpoint Template, appeal to ethos. Center For The Arts | Seating Charts! Throughout the rest of his speech he would keep up this type of appeal, preferring the approach of ethical appeals to that of logic. Due to his lack of Forest Snow Powerpoint Template, | 02888, logical appeals, he seemed to Fascinating Resume Sample revert to logical. Appeal to emotion , Argument , Argumentation theory 1132 Words | 3 Pages. *Metaphors or Arguments * Metaphors are an important ingredient to Forest Snow Template, Backgrounds speech and argument . It is Advertisement Essay used to show comparison between . Forest Snow Template, Backgrounds! two things, a way to create new meaning.
Niccolo Machiavelli in his book The Prince discuss of social and political along with his creative usage of metaphors. His ideas consist of Medicine, the Fox and the Lion, as well as The Archer. These are the metaphors that I will be discussing as we go in more debt about Machiavelli and James Kastely thoughts of argument . Machiavelli. Analogy , Archery , Argument 922 Words | 3 Pages. ?Among Immanuel Kant's (1724–1804) most influential contributions to philosophy is his development of the transcendental argument . Level Pdf,! In Kant's . conception, an argument of this kind begins with a compelling premise about our thought, experience, or knowledge, and then reasons to Forest Snow Powerpoint Template, Backgrounds | 02888 a conclusion that is a substantive and unobvious presupposition and necessary condition of this premise. Medical Assistant Tips! The crucial steps in Forest Powerpoint | 02888, this reasoning are claims to the effect that a subconclusion or conclusion is a presupposition and. Argument , Critique of Pure Reason , Epistemology 2045 Words | 5 Pages. Descartes Dream Argument - Philosophy. are having, or we are not dreaming all our experience of this world? When we dream we imagine things happening often with the same sense of reality as we do . when we are awake. In Descartes dream argument , he states there are no reliable signs distinguishing sleeping from waking.
In his dream argument , he is not saying we are merely dreaming all of what we experience, nor, is he saying we can distinguish dreaming from being awake. I think his point is we cannot be for sure what we experience as. Argument , Dream , Dreaming 1410 Words | 4 Pages. to have many books on the “Best-Selling” List. In her book, “The Argument Culture”, Deborah Tannen takes a closer look at how we as a society . Medical Administrative Best Resume! have come to view arguing/debating as a normal form of communication. Our inability to look at more than two views at a time, has led us to limit the potential conversations that could easily take place.
In this essay, Professor Tannen takes a shot at making us believe that being in an “ Argument -culture” is not the best thing for us as a whole. Snow | 02888! She wants us to. Argument , Argumentation theory , Arguments 1157 Words | 5 Pages. This revision looks more closely at the second purpose of writing which is examined in Standard Grade English - to deploy ideas and argue. This means that . The Creative Entrepreneur Checklist:! you are expected to discuss a given topic and to present an Forest Snow Powerpoint | 02888 argument related to it. Fascinating Legal 4 Legal Resume Sample! Organising a discursive essay There are three basic structures (ways of organising) for Snow Powerpoint Backgrounds, the discursive essay - * you argue strongly for a given discussion topic * you argue strongly against a given discussion topic * you argue about a given discussion. Animal testing , Argument , Arguments 1703 Words | 5 Pages. Argument for Paying College Athletes.
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