Using mention accessibility to improve coreference resolution
| Autor: | Kellie Webster, Joel Nothman |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
03 medical and health sciences
Coreference 0302 clinical medicine Information retrieval Computer science 030221 ophthalmology & optometry 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing General knowledge 02 engineering and technology Resolution (logic) Baseline (configuration management) |
| Zdroj: | ACL (2) |
| Popis: | Modern coreference resolution systems require linguistic and general knowledge typically sourced from costly, manually curated resources. Despite their intuitive appeal, results have been mixed. In this work, we instead implement fine-grained surface-level features motivated by cognitive theory. Our novel fine-grained feature specialisation approach significantly improves the performance of a strong baseline, achieving state-of-the-art results of 65.29 and 61.13% on CoNLL-2012 using gold and automatic preprocessing, with system extracted mentions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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