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イベント共参照関係を利用した因果関係知識の獲得
http://hdl.handle.net/2261/51736
http://hdl.handle.net/2261/517363514e67d-30e4-4b45-9bdc-6f836da6d2ec
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
48106422.pdf (763.5 kB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2012-05-29 | |||||
| タイトル | ||||||
| タイトル | イベント共参照関係を利用した因果関係知識の獲得 | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| 資源タイプ | ||||||
| 資源 | http://purl.org/coar/resource_type/c_46ec | |||||
| タイプ | thesis | |||||
| その他のタイトル | ||||||
| その他のタイトル | Extracting Causal Relation using Event Coreference | |||||
| 著者 |
田中, 翔平
× 田中, 翔平 |
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| 著者別名 | ||||||
| 識別子Scheme | WEKO | |||||
| 識別子 | 8199 | |||||
| 姓名 | Tanaka, Shohei | |||||
| 著者所属 | ||||||
| 著者所属 | 東京大学大学院情報理工学系研究科電子情報学専攻 | |||||
| 著者所属 | ||||||
| 著者所属 | Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo | |||||
| Abstract | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Causal relations are essential knowledge for interpreting discourse structure of text. This paper presents a method that extracts causal relations of lexical patterns in the form of quasi Horn clauses: for example, "A acquires B" AND "B is located in X"→"the acquisition gives A operations in X". The input of the method is a relation tuple consisting of two entities and a verb, e.g., (A, acquire, B). The method finds coreferencial expressions of the given relation that mention the same event. We use nominal forms of verbs included in FrameNet for finding the coreference expression. If a nominal form of a relation occurs as the subject in the dependency tree of a sentence, the sentence is likely to describe what is caused by the event. Then the method uses several NLP techniques (part-of-speech tagging, coreference resolution, dependency parsing and named entity recognition) in order to build a lexical pattern containing the entities (A and B). However, such rules are so specific that computers cannot reuse the knowledge of causality relation: for example, "the acquisition gives A operations in Nevada". Therefore, the proposed method generalize the rules by introducing a variable X and estimating the relation between X and A or between X and B. For evaluation, we asked human annotators to judge the correctness of the causal-relation rules. The result shows that the proposed method precisely extracts the causal-relation rules. | |||||
| 書誌情報 | 発行日 2012-03-22 | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 007 | |||||
| 学位名 | ||||||
| 学位名 | 修士(情報理工学) | |||||
| 学位 | ||||||
| 値 | master | |||||
| 研究科・専攻 | ||||||
| 情報理工学系研究科電子情報学専攻 | ||||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2012-03-22 | |||||
