Usage disambiguation of Turkish discourse connectives.
This paper describes a rule-based approach and a machine learning approach to disambiguate the discourse usage of Turkish connectives, which not only has single and phrasal connectives as most languages do, but also suffixal connectives that largely correspond to subordinating conjunctions in Englis...
| Publicado en: | Language Resources & Evaluation Vol. 57; no. 1; pp. 223 - 257 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Mar2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=162506766&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 162506766 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2023 vid: 57 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 162506766 10.1007/s10579-022-09614-3 ppf: 223 ppct: 34 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2MB tig: atl: Usage disambiguation of Turkish discourse connectives. aug: au: Başıbüyük, Kezban Zeyrek, Deniz affil: Department of Computer Engineering, Middle East Technical University, 06800, Ankara, Turkey Cognitive Science Department, Graduate School of Informatics, Middle East Technical University, 06800, Ankara, Turkey su: Discourse markers Machine learning English language sug: subj: Discourse markers Machine learning English language keyword: Connective lexicon Discourse connectives Discourse processing Turkish Usage disambiguation ab: This paper describes a rule-based approach and a machine learning approach to disambiguate the discourse usage of Turkish connectives, which not only has single and phrasal connectives as most languages do, but also suffixal connectives that largely correspond to subordinating conjunctions in English. Since these connectives have different linguistic characteristics, two sets of linguistic rules are devised to disambiguate their discourse usage. The linguistic rules are used in the rule-based approach and employed as feature sets in the machine learning approach to test whether they influenced the decision of our algorithms. The results of both approaches are evaluated over the Turkish section of TED-Multilingual Discourse Bank and Turkish Discourse Bank 1.1, two datasets annotated in the Penn Discourse TreeBank style. The paper attests to the predictive power of the linguistic rules in disambiguating the discourse usage of both types of connectives also offering new knowledge and insights for discourse processing from the view of a morphologically rich language. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2023. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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