TY - JOUR AU - Allen, James AU - Bahkshandeh, Omid AU - de Beaumont, William AU - Galescu, Lucian AU - Teng, Choh Man PY - 2018/04/26 Y2 - 2024/03/29 TI - Effective Broad-Coverage Deep Parsing JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 32 IS - 1 SE - Main Track: NLP and Knowledge Representation DO - 10.1609/aaai.v32i1.11934 UR - https://ojs.aaai.org/index.php/AAAI/article/view/11934 SP - AB - <p> Current semantic parsers either compute shallow representations over a wide range of input, or deeper representations in very limited domains. We describe a system that provides broad-coverage, deep semantic parsing designed to work in any domain using a core domain-general lexicon, ontology and grammar. This paper discusses how this core system can be customized for a particularly challenging domain, namely reading research papers in biology. We evaluate these customizations with some ablation experiments </p> ER -