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Design and Preparation of a Persian Semantic Corpus Using Abstract Meaning Representation

Takhshid, Reza | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55514 (31)
  4. University: Sharif University of Technology
  5. Department: Languages and Linguistics Center
  6. Advisor(s): Bahrani, Mohammad; Shojaie, Razieh
  7. Abstract:
  8. To keep in line with the day to day advancements in the fields of computational linguistics and natural language processing, and the growing attention of researchers to semantic processing, this thesis presents the design and preparation of a Persian semantic corpus using Abstract Meaning Representation (AMR). This semantic representation pairs each sentence with a single rooted, acyclic, directed graph, which is human and computer readable. Moreover, this representation paves the way for the creation of large semantic corpora. In order to bring such benefits to Persian, in this thesis we present solutions for representing Persian sentences in the framework of AMR. Moreover, a corpus of 150 Persian sentences paired with their Persian AMR graphs with the inter-annotator agreement of 81\% is represented, which shows the effectiveness of the prepared Persian AMR specification. With the goal of expanding the size of the corpus, a rule-based convertor has been designed and implemented. Using the converter, over 5000 Persian AMR graphs have been converted from a Persian proposition bank. The accuracy of these sentences compared with the gold graphs is 61\%
  9. Keywords:
  10. Abstract Meaning Representation ; Persian Abstract Meaning Representation ; Semantic Graph ; Semantic Representation ; Semantic Proccesing

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