CSA2050 Introduction to Computational Linguistics

1. CSA2050 Introduction to Computational Linguistics Lecture DCG3 Handling Subcategorisation Handling Relative Clauses CSA2050: DCG3

2. Subcategories of Verbs • English includes the following sentences: • John disappeared • John broke the window • John gave Mary the book • In each case the verb phrase has a different structure corresponding to the number of noun phrases that follow. CSA2050: DCG3

3. Subcategories of VP VP V disappeared VP V NP broke the window VP V NP NP gave Mary the book • To handle this we need separate rules for VP CSA2050: DCG3

4. Some Rules forSubcategories of Verb vp -> v. vp -> v, np. vp -> v, np, np. • Checkpoint: how good are these rules for handling English? CSA2050: DCG3

5. Counterexamples • The following sentences obey the above rules: • John broke • Mary disappeared the window • Mike told Mary the book • All of them violate the subcategorisation constraints of the individual verbs. • How can we make sure that the right rule goes with the right verb? CSA2050: DCG3

6. Handling Subcategorisation - I vp --> v1. vp --> v2, np. vp --> v3 np, np. • This solution has the problem that the vi are distinct symbols with no relationship between them. We thus miss the fact that they are all verbs CSA2050: DCG3

7. Handling Subcategorisation - II • A slightly better method is to adopt rules of the following shape: vp --> v(intrans) vp --> v(trans), np. vp --> v(ditrans), np, np. • This is essentially the same method that we used to avoid multiplying categories when handling agreement. CSA2050: DCG3

8. Handling Subcategorisation:The Lexicon • Assume that the lexicon looks something like this: lex(disappeared, v, intrans). lex(broke,v, trans). lex(gave, v, ditrans). CSA2050: DCG3

9. Two Approaches – One Lexicon • Approach 1 v1 --> [X] {lex(X,v,intrans)}. v2 --> [X] {lex(X,v,trans)}. v2 --> [X] {lex(X,v,ditrans)}. • Approach 2 v(Type) --> [X], {lex(X,v,Type)}. CSA2050: DCG3

10. Other Verb Complements • So far we have only discussed three possible VP rules. But in practice there are many more: • np, pp: John told Bill about the accident • np, vp: John persuaded Bill to come • np, pp,pp: John rented an apartment to Bill for Lm100 • np, s: John informed Bill that Jack was coming • Taking prepositions into account, about 40 different patterns are required to handle verbs in English. • This will lead to an undesirable proliferation of grammar rules. CSA2050: DCG3

11. Subcategorisation:Approach III • Shift responsibility towards the lexicon • Key idea: lexical entry for each verb contains a complement list.lex(told,v, [np,pp]).lex(persuaded,v,[np,vp]).lex(rented,v,[np,pp,pp]. • The list is then managed by the grammar. CSA2050: DCG3

12. Grammar Rules for VP • Basic idea is to avoid multiple grammar rules of the form vp --> v([]). vp --> v([np]), np(...). vp --> v([np,np]), np(...), np(...). vp --> v([np,pp]), np(...), pp(...). vp --> v([np,s]), np(...), s(...). • Instead have a single rule of this formvp --> v(SubCatList), comps(SubCatList).which allows a verb phrase to be formed from a verb followed by a sequence of zero or more complements. CSA2050: DCG3

13. The Grammar s --> np, vp. np --> n. np --> d, n. vp --> v(SC), comps(SC). comps([]) --> []. comps([X|R]) --> x(X), comps(R). CSA2050: DCG3

14. The Comps Rule comps([]) --> []. comps([X|R]) --> x(X), comps(R) • Challenge: how to write the definition of the "x" predicate. CSA2050: DCG3

15. Relative Clauses • Sentences likeTerry runs a program that Bertrand wroteThe man who came to dinner vomitedinclude relative clauses (shown in boldface) • Relative clauses are interesting because they involve "filler-gap dependency" CSA2050: DCG3

16. Structure of Relative Clauses • Relative clauses such asthat Bertrand wroteare not well described byrelclause --> [that], vp. • This is because the underlying structure is not the concatenation of "that" and a VP, i.e. • If this is not the structure, what is? CSA2050: DCG3

17. The Structure of the Relative Clause • To understand the structure we must first look at the wider context in which it occurs, in this case the noun phrase:a program that Bertrand wrote. • This noun phrase is derived from the underlying sentenceBertrand wrote a program. CSA2050: DCG3

18. Derivation of Relative Clause • Basic sentence: Bertrand wrote a program • Step 1: identify object NPBertrand wrote [a program] • Step 2: move to the front, leaving gap where object NP was.[A program] Bertrand wrote npgap • Note that underlined structure is a sentence with a gap instead of an object. • Step 3: insert relative pronoun just before sentence containing gap. • [A program] that Bertrand wrote npgap • N.B. Gap is invisible CSA2050: DCG3

19. Structure of the Noun Phrase NP RelCl d N rel Sgap a program that NP VPgap filler n v NPgap bertrand wrote gap CSA2050: DCG3

20. Long Distance Dependencies • A filler-gap dependency occurs in an NL sentence when a subpart of some phrase is missing from its normal location and another phrase, outside the incomplete one, stands in its place. • Filler-gap dependencies are examples of long-distance dependencies. • The amount of material between dependents (in this case filler and gap) is unbounded, at least in principle, e.g.Terry read a book that Bertrand told a student to ask a professor to write. CSA2050: DCG3

21. Handling Gaps within a DCG • Use a nonterminal argument position to indicate the presence or absence a gap, e.g.np(nogap) = an NP without a gapnp(gap) = an NP with a gap • Introduce the term gap(T) to indicate the presence or absence of a gap of category T. So gap(np) will indicate where an NP used to be. • For each category c that admits gaps, introduce the rule c(gap(c)) rewrites nothing, e.g.np(gap(np)) --> [ ]. CSA2050: DCG3