1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Spring 2006-Lecture 2

2 Outline of English syntax Words Phrases Simple Sentences

3 Review What is computational linguistics? What is the subject matter of theoretical computational linguistics? What is the subject matter of applied computational linguistics? Why is language hard for the computer?

4 Review Give examples of –Syntactic ambiguity –Semantic ambiguity –Phonological ambiguity

5 Words Two basic ways to form words –Inflectional (e.g. English verbs) Open + ed = opened Open + ing = opening –Derivational (e.g. adverbs from adjectives, nouns from adjectives) Happy  happily Happy  happiness (nouns from adjectives)

6 Basic classes of words Classes of words aka parts of speech (POS) –Nouns –Verbs –Adjectives –Adverbs The above classes of word belong to the type open class words We also have closed class words –Articles, pronouns, prepositions, particles, quantifiers, conjunctions

7 Basic phrases A word from an open class can be used to form the basis of a phrase The basis of a phrase is called the head

8 Examples of phrases Noun phrases –The manager of the institute –Her worry to pass the exams –Several students from the English Department Adjective phrases –easy to understand –mad as a dog –glad that he passed the exam

9 Examples of phrases Adverb phrases –fast like the wind –outside the building Verb phrases –ate her sandwich –went to the doctor –believed what I told him

10 “Complements” Notice that to be meaningful the verb “go”, for example requires a phrase for “location” –*John went –John went home Such phrases “complete” the meaning of the verb (or other type of head) and are called complements

11 Inside the noun phrase NPs are used to refer to things: objects, places, concepts, events, qualities, etc NPs may consist of: –A single pronoun (he, she, etc) –A name or proper noun (John, Athens, etc) –A specifier and a noun –A qualifier and a noun –A specifier and a qualifier and a noun (e.g., the first three winners)

12 Specifiers Specifiers indicate how many objects are described and also how these objects relate to the speaker Basis types of specifiers –Ordinals (e.g., first, second) –Cardinals (e.g., one, two) –Determiners (see next slide)

13 Determiners Basic types of determiners –Articles (the, a, an) –Demonstratives (this, that, these, those) –Possessives (‘s, her, my, whose, etc) –Wh-determiners (which, what –in questions) –Quantifying determiners (some, every, most, no, any etc)

14 Qualifiers Basic types of qualifiers –Adjectives Happy cat Angry feelings –Noun modifiers Cook book University hospitals

15 Inside the verb phrase A simple VP –Adverbial modifier + head verb + complements Types of verbs –Auxiliary (be, do, have) –Modal (will, can, could) –Main (eat, work, think)

16 Types of verb complements Intransitive verbs do not required complements Transitive verbs require an object as a complement (e.g. find a key) Transitive verbs allow passive forms (e.g. a key was found) Ditransitive verbs require one direct and on indirect object (e.g. give Mary a book)

17 Other verb complements Clausal complements –Some verbs require clausal complements Mary knows that John left Prepositional phrase complements –Some verbs requires specific PP complements Mary gave the book to John –Others require any PP complement John put the book on the shelf/in the room/under the table

18 Adjective phrases Simple –Angry, easy, etc Complex –Pleased with the prize –Angry at the committee –Willing to read the book Complex AdjP normally do not precede nouns, they are used as complements of verbs such as be or seem

19 Adverbial phrases Indicators of –Degree –Location –Manner –The time of something (now, yesterday, etc) –Frequency –Duration Location in the sentence –Initial –Medial –Final

20 The famous argument-adjunct problem Sometimes it’s hard to say if an adverbial is a verb complement (i.e. it’s an argument of the verb) or simply a modification of the verb phrase (i.e. an adjunct) Consider –Mary put the book on the shelf –*Mary put –Mary painted the room with a brush –Mary painted the room

21 Grammars and parsing What is syntactic parsing –Determining the syntactic structure of a sentence Basic steps –Identify sentence boundaries –Identify what part of speech is each word –Identify syntactic relations

22 Tree representation John ate the pizza (S (NP (N John)) (VP (V ate) (NP (Det the) (N cat))))

23 Some basic tree terminology Nodes Links Root Leaves Parent node Child node Ancestor The notion of “domination”

24 How to construct a tree To construct a tree of an English sentence you need to know which structure are legal in English Rewrite rules –Describe what tree structures are allowed in the language

25 Rewrite rules for English NP==> N NP==> Det NP VP==> V VP ==> V NP S ==> NP VP S ==> NP VP ==> N VP ==> John VP ==> John V NP ==> John ate NP ==> John ate Det N ==> John ate the N ==> John ate the pizza

26 What makes a good grammar? Generality –The range of sentences covered by the rules Selectivity –The range of sentences that can be identified as ungrammatical Understandability –How simple the grammar is

27 Hint for making rules general Pay attention to constituents Diagnostic of constituency –Conjunction Compare –I ate a hamburger and a hot dog –I will eat the hamburger and throw away the hot dog –I ate a hamburger and John ate a hot dog –*I ate a hamburger and on the stove –*I ate a cold hot dog and well burned –*I ate the hot dog

28 How the conjunction test can help Compare –I looked up John’s number –I looked up John’s chimney –*I looked up John’s number and in his cupboards –I looked up John’s chimney and in his cupboards

29 Parsing strategies Top-down –A top down parser starts with S and attempts to rewrite it into a sequence of terminal symbols that matches the words in the input sentence Bottom-up –You take a sequence of symbols and match it to the right hand side of the rule, i.e. start with Det N and match it to get the NP Bottom-up chart parsing –To avoid unnecessary repetition of the matching process you use a data structure called chart that allows you to record partial results We’ll see examples in J. Allen’s Natural Language Understanding, Chapter 3

30 What is generative capacity? The range of languages that a formalism can describe Formal languages allow a precise (mathematic) characterization Natural languages CANNOT be characterized precisely enough to define generative capacity