1. CS626-460: Language Technology for the Web/Natural Language Processing Pushpak Bhattacharyya CSE Dept., IIT Bombay Parsing Algos

2. A segment of English Grammar S’  (C) S S  {NP/S’} VP VP  (AP+) (VAUX) V (AP+) ({NP/S’}) (AP+) (PP+) (AP+) NP  (D) (AP+) N (PP+) PP  P NP AP  (AP) A

3. Example Sentence People laugh 1 2 3 Lexicon: People - N, V Laugh - N, V These are positions This indicate that both Noun and Verb is possible for the word “People”

4. Top-Down Parsing State Backup State Action ----------------------------------------------------------------------------------------------------- 1.((S) 1) - - 2. ((NP VP)1) - - 3a. ((DT N VP)1) ((N VP) 1) - 3b. ((N VP)1) - - 4. ((VP)2) - Consume “People” 5a. ((V ADV)2) ((V)2) - 6. ((ADV)3) ((V)2) Consume “laugh” 5b. ((V)2) - - 6. ((.)3) - Consume “laugh” Termination Condition : All inputs over. No symbols remaining. Note: Input symbols can be pushed back. Position of input pointer

5. Discussion for Top-Down Parsing This kind of searching is goal driven. Gives importance to textual precedence (rule precedence). No regard for data, a priori (useless expansions made).

6. Bottom-Up Parsing Some conventions: N 12 S 1? -> NP 12 ° VP 2? Represents positions End position unknown Work on the LHS done, while the work on RHS remaining

7. Bottom-Up Parsing (pictorial representation) S -> NP 12 VP 23 ° People Laugh 1 2 3 N 12 N 23 V 12 V 23 NP 12 -> N 12 ° NP 23 -> N 23 ° VP 12 -> V 12 ° VP 23 -> V 23 ° S 1? -> NP 12 ° VP 2?

8. Problem with Top-Down Parsing Left Recursion Suppose you have A-> AB rule. Then we will have the expansion as follows: ((A)K) -> ((AB)K) -> ((ABB)K) ……..

9. Combining top-down and bottom-up strategies

10. Top-Down Bottom-Up Chart Parsing Combines advantages of top-down & bottom- up parsing. Does not work in case of left recursion. e.g. – “People laugh” People – noun, verb Laugh – noun, verb Grammar – S  NP VP NP  DT N | N VP  V ADV | V

11. Transitive Closure People laugh 123 S  NP VPNP  N  VP  V  NP  DT NS  NP  VPS  NP VP  NP  NVP  V ADVsuccess VP  V

12. Arcs in Parsing Each arc represents a chart which records Completed work (left of  ) Expected work (right of  )

13. Example People laughloudly 1234 S  NP VPNP  N  VP  V  VP  V ADV  NP  DT NS  NP  VPVP  V  ADVS  NP VP  NP  NVP   V ADVS  NP VP  VP   V

14. Dealing With Structural Ambiguity Multiple parses for a sentence The man saw the boy with a telescope. The man saw the mountain with a telescope. The man saw the boy with the ponytail. At the level of syntax, all these sentences are ambiguous. But semantics can disambiguate 2 nd & 3 rd sentence.

15. Prepositional Phrase (PP) Attachment Problem V – NP 1 – P – NP 2 (Here P means preposition) NP 2 attaches to NP 1 ? or NP 2 attaches to V ?

16. Parse Trees for a Structurally Ambiguous Sentence Let the grammar be – S  NP VP NP  DT N | DT N PP PP  P NP VP  V NP PP | V NP For the sentence, “I saw a boy with a telescope”

17. Parse Tree - 1 S NPVP NVNP DetNPP PNP DetN I saw a boy with atelescope

18. Parse Tree -2 S NPVP NVNP DetN PP PNP DetN I saw a boy with atelescope

19. Exercise For the sentence, “The man saw the boy with a telescope” & the grammar given previously, compare the performance of top-down, bottom-up & top-down chart parsing.

20. Verb Alternation (1/2) (ref: Natural Language Understanding, James Allan) VerbComplement Structure Example laughEmpty (in transitive)Ram laughed findNP (transitive)Ram found the key giveNP+NP (di transitive)Ram gave Sita the paper giveNP+PP [to]Ram gave the paper to Sita ResideLoc PhraseRam resides in Mumbai putNP+loc phraseRam put the book inside the box speakPP [with]+PP[about]Ram with Sita about floods tryVP[to]Ram tried to apologise tellNP+VP[to]Ram told the man to go

21. Verb Alternation (1/2) VerbComplement Structure Example wishS [to]Ram wished for the man to go keepVP [ing]Ram keeps hoping for the best catchNP+VP [ing]Ram caught Shyam looking in his desk WatchNP+VP [base]Ram watched Shyam eat the pizza regretS [that]Ram regretted that he had eaten the whole thing TellNP+S [that]Ram told Sita that he was sorry SeemADJPRam seems unhappy in his new job ThinkNP+ADJPRam thinks Sita is happy KnowS [wh]Ram knows where to go