Accepted author manuscript, 91.7 KB, PDF document
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - The UCREL semantic analysis system.
AU - Rayson, P.
AU - Archer, Dawn
AU - Piao, S.
AU - McEnery, A. M.
PY - 2004
Y1 - 2004
N2 - The UCREL semantic analysis system (USAS) is a software tool for undertaking the automatic semantic analysis of English spoken and written data. This paper describes the software system, and the hierarchical semantic tag set containing 21 major discourse fields and 232 fine-grained semantic field tags. We discuss the manually constructed lexical resources on which the system relies, and the seven disambiguation methods including part-of-speech tagging, general likelihood ranking, multi-word-expression extraction, domain of discourse identification, and contextual rules. We report an evaluation of the accuracy of the system compared to a manually tagged test corpus on which the USAS software obtained a precision value of 91%. Finally, we make reference to the applications of the system in corpus linguistics, content analysis, software engineering, and electronic dictionaries
AB - The UCREL semantic analysis system (USAS) is a software tool for undertaking the automatic semantic analysis of English spoken and written data. This paper describes the software system, and the hierarchical semantic tag set containing 21 major discourse fields and 232 fine-grained semantic field tags. We discuss the manually constructed lexical resources on which the system relies, and the seven disambiguation methods including part-of-speech tagging, general likelihood ranking, multi-word-expression extraction, domain of discourse identification, and contextual rules. We report an evaluation of the accuracy of the system compared to a manually tagged test corpus on which the USAS software obtained a precision value of 91%. Finally, we make reference to the applications of the system in corpus linguistics, content analysis, software engineering, and electronic dictionaries
M3 - Conference contribution/Paper
SP - 7
EP - 12
BT - Proceedings of the beyond named entity recognition semantic labelling for NLP tasks workshop, Lisbon, Portugal, 2004
CY - Lisbon
T2 - Beyond Named Entity Recognition Semantic labelling for NLP tasks
Y2 - 25 May 2004 through 25 May 2004
ER -