Constructing a WordNet for Turkish Using Manual and Automatic Annotation
| Autor: | Razieh Ehsani, Olcay Taner Yildiz, Ercan Solak |
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| Přispěvatelé: | Işık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Computer Engineering, Ehsani, Razieh, Solak, Ercan, Yıldız, Olcay Taner |
| Rok vydání: | 2018 |
| Předmět: |
Connected component
General Computer Science Zipf's law Turkish business.industry Computer science WordNet 02 engineering and technology computer.software_genre language.human_language Lexicography Annotation Synset 020204 information systems 0202 electrical engineering electronic engineering information engineering language 020201 artificial intelligence & image processing Artificial intelligence Variation of information business Cluster analysis computer Natural language processing |
| Zdroj: | ACM Transactions on Asian and Low-Resource Language Information Processing. 17:1-15 |
| ISSN: | 2375-4702 2375-4699 |
| Popis: | In this article, we summarize the methodology and the results of our 2-year-long efforts to construct a comprehensive WordNet for Turkish. In our approach, we mine a dictionary for synonym candidate pairs and manually mark the senses in which the candidates are synonymous. We marked every pair twice by different human annotators. We derive the synsets by finding the connected components of the graph whose edges are synonym senses. We also mined Turkish Wikipedia for hypernym relations among the senses. We analyzed the resulting WordNet to highlight the difficulties brought about by the dictionary construction methods of lexicographers. After splitting the unusually large synsets, we used random walk-based clustering that resulted in a Zipfian distribution of synset sizes. We compared our results to BalkaNet and automatic thesaurus construction methods using variation of information metric. Our Turkish WordNet is available online. Publisher's Version |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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