Detection of inconsistencies in concept classifications in a large dictionary — Toward an improvement of the EDR electronic dictionary —

Eiko Yamamoto, Kyoko Kanzaki, Hitoshi Isahara


Abstract
The EDR electronic dictionary is a machine-tractable dictionary developed for advanced computer-based processing of natural lan-guage. This dictionary comprises eleven sub-dictionaries, including a concept dictionary, word dictionaries, bilingual dictionaries, co-occurrence dictionaries, and a technical terminology dictionary. In this study, we focus on the concept dictionary and aim to revise the arrangement of concepts for improving the EDR electronic dictionary. We believe that unsuitable concepts in a class differ from other concepts in the same class from an abstract perspective. From this notion, we first try to automatically extract those concepts unsuited to the class. We then try semi-automatically to amend the concept explications used to explain the meanings to human users and rearrange them in suitable classes. In the experiment, we try to revise those concepts that are the lower-concepts of the concept “human” in the concept hierarchy and that are directly arranged under concepts with concept explications such as “person as defined by –” and “person viewed from –.” We analyze the result and evaluate our approach.
Anthology ID:
L06-1373
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/613_pdf.pdf
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http://www.lrec-conf.org/proceedings/lrec2006/pdf/613_pdf.pdf