Earlier chapters focused on words: We have also seen how to identify patterns in word sequences or n-grams. However, these methods only scratch the surface of the complex constraints that govern sentences. We need a way to deal with the ambiguity that natural language is famous for.
We also need to be able to cope with the fact that there are an unlimited number of possible sentences, and we can only write finite programs to analyze their structures and discover their meanings. Along the way, we will cover the fundamentals of English syntax, and see that there are systematic aspects of meaning that are much easier to capture once we have identified the structure of sentences.
Previous chapters have shown you how to process and analyse text corpora, and we here stressed the challenges for NLP in dealing with the vast amount of electronic language data that is How To Write 3 Tree For Loop Shorter daily. Let's consider this data more closely, and make the thought experiment that we have a gigantic corpus consisting of everything that has been either uttered or written in English over, say, the last 50 years.
Would we be justified in calling this corpus "the language of modern English"? There are a number of reasons why we might answer No. Recall that in 3we asked you to search the web for instances of the pattern the of.
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Although it is easy to find examples on the web containing this word sequence, such as New man at the of IMG http: Accordingly, we can argue that the "modern English" is not equivalent to the very big set of word sequences in our imaginary corpus. Speakers of English can make judgements about these sequences, and will reject some of them as being ungrammatical.
Equally, it is easy to compose a new sentence and have speakers agree that it is perfectly good English. For example, sentences have an interesting property that they can be embedded inside larger sentences. Consider the following sentences:. Usain Bolt broke the m record. The Jamaica Observer reported that Usain Bolt broke the m record.
If we replaced whole sentences with the symbol Swe would see patterns like Andre said S and I think S. These are templates for taking a sentence and constructing a bigger sentence.
There are other templates we can use, like S but Sand S when S. With a bit of ingenuity we can construct some really long sentences using these templates.
Here's an impressive example from a Winnie the Pooh story by A. This long sentence actually has a simple structure that begins S but S when S. We can see from this example that language provides us with constructions which seem to allow us to extend sentences indefinitely.
It is also striking that we can understand sentences of arbitrary length that we've never heard before: The purpose of a grammar is to give an explicit description of a language. But the way in which we think of a grammar is closely intertwined with what we consider to be a language. Is it a large but finite set of observed utterances and written texts?
Is it something more abstract like the implicit knowledge that competent speakers have about grammatical sentences?
Or is it some combination of the two? We won't take a stand on this issue, but instead will introduce the main approaches. In this chapter, we will adopt the formal framework of "generative grammar", in which a "language" is considered to be nothing more than an enormous collection of all grammatical sentences, and a grammar is a formal notation that can be used for "generating" the members of this set. A well-known example of ambiguity is shown in 2from the Groucho Marx movie, Animal Crackers How he got into my pajamas, I don't know.
Let's take a closer look at the ambiguity in the phrase: I shot an elephant in my pajamas. First we need to define a simple grammar:. This grammar permits the sentence to be analyzed in two ways, depending on whether the prepositional phrase in my pajamas describes the elephant or the shooting event.
The program produces two bracketed structures, which we can depict as trees, as shown in 3b:. Notice that there's no ambiguity concerning the meaning of any of the words; e. Consider the following sentences and see if you can think of two quite different interpretations: Fighting animals could be dangerous.
Visiting relatives can be tiresome. Is ambiguity of the individual words to blame? If not, what is the cause of the ambiguity? This chapter presents grammars and parsing, as the formal and computational methods for investigating and modeling the linguistic phenomena we have been discussing. As we shall see, patterns of well-formedness and ill-formedness in a sequence of words can be understood with respect to the phrase structure and dependencies.
We can develop formal models of these structures using grammars and parsers. As before, a key motivation is natural language How To Write 3 Tree For Loop Shorter. How much more of the meaning of a text can we access when we can reliably recognize the linguistic structures it contains? Having read in a text, can a program "understand" it enough to be able to answer simple questions about "what happened" or "who did what to whom"?
Also as before, we will develop simple programs to process annotated corpora and perform useful tasks. We gave an example in 2. Here's another pair of examples that we created check this out computing the bigrams over the text of a childrens' story, The Adventures of Buster Brown http: He roared with me the pail slip down his back.
The worst part and clumsy looking for whoever heard light. You intuitively know that these sequences are "word-salad", but you probably find it hard to pin down what's wrong with them.
One benefit of studying grammar is that it provides a conceptual framework and vocabulary for spelling click these intuitions.
Let's take a closer look at the sequence the worst part and clumsy looking. This looks like a coordinate structurewhere two phrases are joined by a coordinating conjunction such as andbut or or. Here's an informal and simplified statement of how coordination works syntactically:. Here are a couple of examples. In the first, two NP s noun phrases have been conjoined to make an NPwhile in the second, two AP s adjective phrases have been conjoined to make an AP. The book's ending was NP the worst part How To Write 3 Tree For Loop Shorter the best part for me.
On land they are AP slow and clumsy looking. What we can't do is conjoin an NP and an APwhich is why the worst part and clumsy looking is ungrammatical. Before we can formalize these ideas, we need to understand the concept of constituent structure.
Constituent structure is based on the observation that words combine with other words to form units. The evidence that a sequence of words forms such a unit is given by substitutability — that is, a sequence of words in a well-formed sentence can be replaced by a shorter sequence without rendering the sentence ill-formed.
To clarify this idea, consider the following sentence:. The fact that we can substitute He for The little bear indicates that the latter sequence is a unit. By contrast, we cannot replace little bear saw in the same way.
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He saw the fine fat trout in the brook. Each sequence that forms a unit can in fact be replaced by a single word, and we end up with just two elements. Substitution of Word Sequences: This diagram reproduces 2. If we now strip out the words apart from the topmost row, add an S node, and flip the figure over, we end up with a standard phrase structure just click for source, shown in 8.
Each node in this tree including the words is called a constituent. As we will see in the next section, a grammar specifies how the sentence can be subdivided into its immediate constituents, and how these can be further subdivided until we reach the level of individual words. How To Write 3 Tree For Loop Shorter we saw in 1sentences can have arbitrary length.
Consequently, phrase structure trees can have arbitrary depth. The cascaded chunk parsers we saw in 4 can only produce structures of bounded depth, so chunking methods aren't applicable here.
Let's start off by looking at a simple context-free grammar. By convention, the left-hand-side of the first production is the start-symbol of the grammar, typically Sand all well-formed trees must have this symbol as their root label.
In NLTK, context-free grammars are defined in the nltk. A Simple Context-Free Grammar. The grammar in 3.
But, yeah, we were stuck there for about 30-40 minutes at least, one woman told Nine. There was grime and dirt on the floors and walls. Tom Brady was selected as Super Bowl LI MVP, but there were several candidates. Once upon a time there was a car that was a boat.
Recursive Descent Parser Demo: This tool allows you to watch the operation of a recursive descent parser as it grows the parse tree and matches it against the input words. Try developing a simple grammar of your own, using the recursive descent parser application, nltk. It comes already loaded with a sample grammar, but you can edit this as you please using the Edit menu.
Change the grammar, and the sentence to be parsed, and run the parser using the autostep button. If we parse the sentence The dog saw a man in the park using the grammar shown in 3. Since our grammar licenses two trees for this sentence, the sentence is said to be structurally ambiguous. The ambiguity in question is called a prepositional phrase attachment ambiguityas we saw earlier in this chapter. As you may recall, it is an ambiguity about attachment since the PP in the park needs to be attached to one of two places in the tree: When the PP is attached to VPthe intended interpretation is that the seeing event happened in the park.