NLP Notes

CLaC PASCAL Algorithm:

- Use the coreference resolution system to produce coreference chains for T, H, T and H as a unit.

- For each sentence, determine Predicate-Argument-Structures (PAS), based on the parsing, NP chunking and verb grouping results.

- Apply cardinality filter (if there exists a numeric value N in H that does not exist in T, return false)

- Convert passive voices into active voices.

- For each PAS pair, compute WN distance for verbs in T and H
If WN distance <= threshold & both PASs are in comparable structures, and If there is coreference between corresponding parts, return true - Apply Be-Heuristic Algorithm if H contains the pattern "X is Y", and
(X is in H) & (X' is in T) and {X, X'} belong to the same inter-sentence coreference chain, and
(Y is in H) & (Y' is in T) and {Y, Y'} belong to the same inter-sentence coreference chain, and
X' corefers with Y'
then return true
return false

Precision: around 0.5
Recall: around 0.2
Accuracy: around 0.55
Confidence-Weighted Score (cws): around 0.55


The Paper: http://www.cs.biu.ac.il/~glikmao/rte05/andreevskaia_et_al.pdf