Comparison Of Turkish Proposition Banks By Frame Matching
| Autor: | Olcay Taner Yildiz, Özge Bakay, Koray Ak |
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| Přispěvatelé: | Işık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Computer Engineering, Ak, Koray, Yıldız, Olcay Taner |
| Rok vydání: | 2018 |
| Předmět: |
Machine translation
Turkish Computer science Natural languages Semantic resources computer.software_genre PropBank Semantic role labeling Statistical machine learning Question answering Learning systems business.industry Multiple languages language.human_language Predicate (grammar) Turkish propbank Machine translations language Artificial intelligence Semantic relations business computer Sentence Natural language Natural language processing |
| Popis: | By indicating semantic relations between a predicate and its associated participants in a sentence and identifying the role-bearing constituents, SRL provides an extensive dataset to understand natural languages and to enhance several NLP applications such as information retrieval, machine translation, information extraction, and question answering. The availability of large resources and the development of statistical machine learning methods have increased the studies in the field of SRL. One of the widely-used semantic resources applied for multiple languages is PropBank. In this paper, PropBanks applied for Turkish are compared by checking semantic roles in the frame files of matched verb senses. As this integrated lexical resource for Turkish is aimed to be used in a multilingual resource along with English, creation of an inclusive lexical resource for Turkish is of great importance. Publisher's Version |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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