Lexical models to improve parse selection

1. GR-Based Improved Parse Selection Sriwantha Sri Aravinda Attanayake University of Cambridge

2. Grammar Relations (GR) Indirect Object John saw a cat with a telescope Subject Determiner

3. Grammar Relations (GR) John saw a cat with a telescope <GR List> (ncsubj saw John ) (iobj saw with ) (dobj saw cat ) (dobj with telescope ) (det telescope a ) (det cat a )

4. Luckily… Parser <GR List> (ncsubj saw John ) (iobj saw with ) (dobj saw cat ) (dobj with telescope ) (det telescope a ) (det cat a )

5. Re Ranking Choice 1 (|ncsubj| |saw| |John| _) (|iobj| |saw| |with|) (|dobj| |saw| |cat|) (|dobj| |with| |telescope|) (|det| |telescope| |a|) (|det| |cat| |a|) Choice 2 (|ncsubj| |saw| |John| _) (|dobj| |saw| |cat|) (|det| |cat| |a|) (|ncmod| _ |cat| |with|) (|dobj| |with| |telescope|) (|det| |telescope| ) Choice 3 (|ncsubj| |saw| |John| _) (|ncmod| _ |saw| |with|) (|dobj| |with| |telescope|) (|det| |telescope| |a|) (|dobj| |saw| |cat|)

6. John saw acatwith a telescope a cat a + cat NP DT+ NN

7. John saw a cat with a telescope Saw + with : 80% cat + with : 40%

8. Parse1 (|ncsubj| |saw| |John| _) (|iobj| |saw| |with|) (|dobj| |saw| |cat|) (|dobj| |with| |telescope|) (|det| |telescope| |a|) (|det| |cat| |a|) Parse 2 (|ncsubj| |saw| |John| _) (|dobj| |saw| |cat|) (|det| |cat| |a|) (|ncmod| |cat| |with|) (|dobj| |with| |telescope|) (|det| |telescope| |a| ) Parse 3 (|ncsubj| |saw| |John| _) (|ncmod| _ |saw| |with|) (|dobj| |with| |telescope|) (|det| |telescope| |a|) (|dobj| |saw| |cat|) Count=1000 Count=5000 2000 100 million wordBritish National Corpus (BNC)

9. F-Score (ncsubj saw John ) 100% accurate, Poor recall (ncsubj saw John ) (iobj saw with ) (dobj saw cat ) (ncsubj saw John ) (iobj saw with ) (dobj saw cat ) (dobj with telescope) (det telescope a ) (det cat a ) 100% recall, Poor accuracy

10. Current Progress F Score Improvement 1% MRR (10 Parses) about 6%

11. Challenges (dobj saw cat ) Count=0 (dobj saw dog) Count=0 (dobj saw it) Count=3 (dobj saw {any word}) Count=45 (dobj of and) Count=170,203 Score= Average (Count)

13. End Production of ssauba2@cam.ac.uk