Semantic Inference at the Lexical-Syntactic Level for Textual Entailment Recognition
What it is about
The paper proposes a proof system for textual entailment that works directly on dependency trees. Entailment rules, manual or acquired from WordNet and from DIRT-style paraphrase data, rewrite the text tree step by step towards the hypothesis, and a cost function measures the remaining distance when no full proof is found. Proofs are limited to depth four, and the parser is Minipar. On the RTE-3 test set the full system reaches 62.4% accuracy with an optimal threshold, and the lexical-only configuration 62.9%, so the richer rules give no consistent gain. On the development set exact proofs have 92% precision but only 4.3% recall; lexical-syntactic rules fire in about 3% of attempted proofs, and missing world knowledge is the main cause of failure.
Ideas
- I1.
en/src/morph.rsand the tree code: a small rule base in the paper's form, a left template matched on a UD tree, a right template generated, and alignment rules that copy the modifiers. Start with the passive-to-active rule and check it on tree pairs built from the school lessons. - I2. Negation and modality as annotation rules: they set features on nodes and block later rewrites (for example under "never"). Measure how many false entailments appear when the blocking is switched off, on a small negative control set.
- I3. Report exact-proof precision and recall separately, and use a cost threshold only when no proof is found, as the paper does. This keeps every "yes" traceable to the rules that produced it.
- I4. A polarity column for complement-taking verbs: "know that p" licenses p in a positive context, "believe that p" does not. Put the list in the complementation chapter and test it on paired sentences.
For Mova
The chapters are 28. Voice and the passive (the passive rule), 27. Negation (negation and polarity) and 23. Complementation (complement polarity). The code is in prag/src/infer.rs and world/src/qa.rs. Measure exact-proof precision and recall on a held-out set of pairs, and run it twice to check determinism.
Cite
@inproceedings{barhaim2007semantic,
title = {{Semantic Inference at the Lexical-Syntactic Level for Textual Entailment Recognition}},
author = {Bar-Haim, Roy and Dagan, Ido and Greental, Iddo and Szpektor, Idan and Friedman, Moshe},
booktitle = {Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing},
year = {2007},
url = {https://aclanthology.org/W07-1422/}
}References
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