This paper presents a supervised approach for identifying generic noun phrases in context. Generic statements express rule-like knowledge about kinds or events. Therefore, their identification is important for the automatic construction of knowledge bases. In particular, the distinction between generic and non-generic statements is crucial for the correct encoding of generic and instance-level information. Generic expressions have been studied extensively in formal semantics. Building on this work, we explore a corpus-based learning approach for identifying generic NPs, using selections of linguistically motivated features. Our results perform well above the baseline and existing prior work.
@inproceedings{ Reiter2010aa,
Title = {{Identifying Generic Noun Phrases}},
Address = { Uppsala, Sweden },
Author = { Nils Reiter and Anette Frank },
Booktitle = {{Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics}},
Pages = { 40-49 },
Publisher = { Association for Computational Linguistics },
Month = { July },
Year = { 2010 }
}
TY -
TI - Identifying Generic Noun Phrases
AU - Nils Reiter
AU - Anette Frank
PY - 2010
CY - Uppsala, Sweden
PB - Association for Computational Linguistics
J2 - Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
ER -