A Corpus-Based Approach for Building Semantic Lexicons
| dc.creator | Riloff, Ellen | |
| dc.creator | Shepherd, Jessica | |
| dc.date | 1997-06-10 | |
| dc.date.accessioned | 2026-07-07T09:10:51Z | |
| dc.date.available | 2026-07-07T09:10:51Z | |
| dc.description | Semantic knowledge can be a great asset to natural language processing systems, but it is usually hand-coded for each application. Although some semantic information is available in general-purpose knowledge bases such as WordNet and Cyc, many applications require domain-specific lexicons that represent words and categories for a particular topic. In this paper, we present a corpus-based method that can be used to build semantic lexicons for specific categories. The input to the system is a small set of seed words for a category and a representative text corpus. The output is a ranked list of words that are associated with the category. A user then reviews the top-ranked words and decides which ones should be entered in the semantic lexicon. In experiments with five categories, users typically found about 60 words per category in 10-15 minutes to build a core semantic lexicon. | |
| dc.description | 8 pages - to appear in Proceedings of EMNLP-2 | |
| dc.identifier | https://arxiv.org/abs/cmp-lg/9706013 | |
| dc.identifier | http://arxiv.org/abs/cmp-lg/9706013 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/151476 | |
| dc.subject | Computation and Language | |
| dc.title | A Corpus-Based Approach for Building Semantic Lexicons | |
| dc.type | text |