Pronominal anaphora resolution in Turkish and English

2023-1-27
Ertan, Melek
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This research analyzes pronominal anaphora in a Turkish and English translated TED corpus, namely the TED-MDB (Zeyrek et al., 2020) and presents a heuristic-based resolution algorithm for resolving pronominal anaphora in these languages separately. The corpus has characteristics of spoken language and has 364 English sentences aligned with their Turkish counterparts. The research is divided into two stages. In the first stage, the data was annotated using a web-based annotation tool INcePTION (Klie et al., 2018). The second phase of the study involves a computational analysis, where the traditional knowledge poor algorithm by Mitkov (1998) was tested on the annotated corpus for Turkish and English separately. The results showed that pronom- inal anaphora can be detected in TED talks with an F1-score of 0.61 in English, and with 0.63 in their Turkish translations.
Anaphora Resolution, computational model, Pronominal Anaphora, knowledge-based model, Natural Language Processing
https://hdl.handle.net/11511/102559
Graduate School of Informatics, Thesis

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Citation Formats
M. Ertan, “Pronominal anaphora resolution in Turkish and English,” M.S. - Master of Science, Middle East Technical University, 2023.
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