HLT

1. HLT Sentence Parsing Algorithms 2 Problems with Depth First Top Down Parsing HLT: Sentence Parsing

2. Left Recursion Handling Ambiguity Inefficiency Problems withDFTD Parser HLT: Sentence Parsing

3. Left Recursion • A grammar is left recursive if it contains at least one non-terminal A for whichA * A and  *  (n.b. * is the transitive closure of ) • Intuitive idea: derivation of that category includes itself along its leftmost branch. NP  NP PP NP  NP and NP NP  DetP Nominal DetP  NP ' s HLT: Sentence Parsing

4. Left Recursion Left recursion can lead to an infinite loop [nltk demo HLT: Sentence Parsing

5. Dealing with Left Recursion • Use different parsing strategy • Reformulate the grammar to eliminate LR A  A |  is rewritten as A  A' A'  A' |  HLT: Sentence Parsing

6. NP → NP ‘and’ NP NP → D N | D N PP Rewriting the Grammar HLT: Sentence Parsing

7. NP → NP ‘and’ NP β NP → D N | D N PP α Rewriting the Grammar HLT: Sentence Parsing

8. NP → NP ‘and’ NP β NP → D N | D N PP α New Grammar NP → αNP1 NP1 → βNP1 | ε Rewriting the Grammar HLT: Sentence Parsing

9. NP → NP ‘and’ NP β NP → D N | D N PP α New Grammar NP → αNP1 NP1 → βNP1 | ε α→ D N | D N PP β→ ‘and’ NP Rewriting the Grammar HLT: Sentence Parsing

10. New Parse Tree NP α NP1 D N the cat ε HLT: Sentence Parsing

11. Rewriting the Grammar • Different parse tree • Unnatural parse tree? HLT: Sentence Parsing

12. Left Corner Parsing • Two kinds of symbol on the stack: “predicted” and “announced”. • The basic idea behind LC parsing is is that when the leftmost child of a production is completed, the parent of the category is “announced”, and the remaining right hand categories are “predicted”. • When a predicted symbol and an announced symbol of the same category are on top of the stack, we can match them and remove them from the stack HLT: Sentence Parsing

13. Left Recursion Handling Ambiguity Inefficiency Problems withDFTD Parser HLT: Sentence Parsing

14. Handling Ambiguity • Coordination Ambiguity: different scope of conjunction:Hot curry and ice taste nice with riceHot curry and rice taste nice with ice • Attachment Ambiguity: a constituent can be added to the parse tree in different places:I shot an elephant in my trousers • VP → VP PPNP → NP PP HLT: Sentence Parsing

15. Real sentences are full of attachment ambiguities President Kennedy today pushed aside other White House business to devote all his time and attention to working on the Berlin crisis address he will deliver tomorrow night to the American peopleover nationwide television and radio HLT: Sentence Parsing

16. Prepositional Phrase Ambiguity • he will deliver • to the American people • over nationwide TV • in New York • during September • for very good reasons HLT: Sentence Parsing

17. Growth of Number of Ambiguities The nth Catalan number counts the ways of dissecting a polygon with n+2 sides into triangles by drawing nonintersecting diagonals. HLT: Sentence Parsing

18. Handling Ambiguities • Statistical disambiguation • which is the most probable interpretation? • Semantic knowledge • which is the most sensible interpretation? • Subatomic particles such as positively charged protons and electrons HLT: Sentence Parsing

19. Left Recursion Handling Ambiguity Inefficiency Problems withDFTD Parser HLT: Sentence Parsing

20. Repeated Parsing of Subtrees • Local versus global ambiguity. • NP → Det Noun • NP → NP PP • Because of the top down depth first, left to right policy, the parser builds trees that fail because they do not cover all of the input. • Successive parses cover larger segments of the input, but these include structures that have already been built before. HLT: Sentence Parsing

21. NP Nom Det Noun a flight Repeated Parsing ofSubtrees NP NP PP Nom DetNoun P Noun aflight from Indianapolis HLT: Sentence Parsing

22. Repeated Parsing ofSubtrees HLT: Sentence Parsing