Name
Abstract | ||
|---|---|---|
Semantic lexical resources play an important part in both linguistic study and natural language engineering. In Lancaster, a large semantic lexical resource has been built over the past 14 years, which provides a knowledge base for the USAS semantic tagger. Capturing semantic lexicological theory and empirical lexical usage information extracted from corpora, the Lancaster semantic lexicon provides a valuable resource for the corpus research and NLP community. In this paper, we evaluate the lexical coverage of the semantic lexicon both in terms of genres and time periods. We conducted the evaluation on test corpora including the BNC sampler, the METER Corpus of law/court journalism reports and some corpora of Newsbooks, prose and fictional works published between 17 th |
Year | Venue | Keywords |
|---|---|---|
2004 | LREC | natural language,knowledge base,information extraction |
Field | DocType | Citations |
Modern English,Annotation,Computer science,Lexicon,Natural language,Semantic lexicon,Artificial intelligence,Natural language processing,Knowledge base,Fictional Works,Semantic computing | Conference | 2 |
PageRank | References | Authors |
0.50 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Scott S. L. Piao | 1 | 93 | 12.65 |
| Paul Rayson | 2 | 538 | 54.59 |
| Dawn Archer | 3 | 32 | 3.31 |
| Tony Mcenery | 4 | 53 | 8.87 |