Compiling English vocabulary lists using machine-readable dictionaries
| Project/Area Number |
15K12889
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
English linguistics
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| Research Institution | Hokkaido University |
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Principal Investigator |
Sonoda Katsuhide 北海道大学, メディア・コミュニケーション研究院, 特任教授 (70113694)
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| Project Period (FY) |
2015-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥130,000 (Direct Cost: ¥100,000、Indirect Cost: ¥30,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
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| Keywords | 英語語彙表 / 機械可読辞書 / 動詞の分類 / LとR / 英語語彙 / 語彙記述 / 動詞分類 / 転換(conversion) / 名詞転換動詞 / 辞書データベース |
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| Outline of Final Research Achievements |
Computational analyses have been carried out of the XML versions of Longman Dictionary of Contemporary English (3rd and 5th eds) with Jupyter Notebook, which is a state-of-the-art Python-programming environment for general data analysis. It has been found out that lexical descriptions in LDOCE are quite reliable linguistically and are based on fairly recent linguistic research. In particular, LDOCE's verb entries include systematic and explicit descriptions of syntactic frames in which the verbs appear for each of their meanings. This has led us to classify English verbs computationally using LDOCE after the fashion of Beth Levin (1993), where she classifies English verbs using diathesis alternations as a main criterion. Together with other analyses, it is demonstrated that computational analyses of dictionary data is essential for improving English vocabulary lists for educational purposes.
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Report
(3 results)
Research Products
(2 results)
