An Empirical Approach to VP Ellipsis

What it is about

Hardt builds the first corpus-based system for resolving VP ellipsis (VPE). The data are 644 VPE examples found in the parsed Penn Treebank, 260 of them from the Wall Street Journal. A syntactic filter first removes candidate antecedents in impossible configurations. The remaining candidates are ranked by four preference factors: recency, clausal relations, parallelism and quotation structure. On a blind test of 96 WSJ examples, the system gets 94.8% head-overlap success, against 75.0% for a recency baseline. Its exact-match accuracy is 76.0%, against 14.6% for the baseline. Human coders agree on the exact match in 93% of cases. Removing the clausal-relation factor drops the score from 75.9% to 72.8%.

Ideas

• I1. en/src/expert.rs: write the syntactic filter as rules over UD trees. Each rule rejects a candidate verb head in a configuration where VPE cannot take it as antecedent, and the rule name is logged in en/src/explain.rs, so every rejection can say why.
• I2. Recency baseline first: report the recency-only score next to the ranked score on the same test set, with the head-overlap and exact-match measures from the paper. A ranker that does not beat recency by a wide margin is not worth its rules.
• I3. Factor ablation on training data only: drop each preference factor in turn, as the paper does for Clause-Rel, and report the drop with en folds. The test set stays held out until the release check.

For Mova

The code is en/src/expert.rs and en/src/explain.rs. The chapter is languages/en/29-ellipsis-word-order-information-structure.md. The Penn Treebank data is licensed, so the paper's numbers are not Mova numbers and no Penn data goes into what is built. Measure first on a VPE set whose licence allows testing: check the licence before any run.

Topics: Coreference resolution

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.5555/972791.972797

@article{hardt1997empirical,
  title = {{An Empirical Approach to VP Ellipsis}},
  author = {Hardt, Daniel},
  journal = {Computational Linguistics},
  year = {1997},
  doi = {10.5555/972791.972797},
  url = {https://doi.org/10.5555/972791.972797}
}

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