SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation
Word Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context. Developing standard WSD test collections can be mentioned as an important prerequisite for developing and evalua...
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University of science and culture
2022-07-01
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| Series: | International Journal of Web Research |
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| Online Access: | https://ijwr.usc.ac.ir/article_165861_444adb5f7ab0eada122fc44b4722aef8.pdf |
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| author | Hossein Rouhizadeh Mehrnoush Shamsfard Vahide Tajalli |
| author_facet | Hossein Rouhizadeh Mehrnoush Shamsfard Vahide Tajalli |
| author_sort | Hossein Rouhizadeh |
| collection | DOAJ |
| description | Word Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context. Developing standard WSD test collections can be mentioned as an important prerequisite for developing and evaluating different WSD systems in the language of interest. Although many WSD test collections have been developed for a variety of languages, no standard All-words WSD benchmark is available for Persian. In this paper, we address this shortage for the Persian language by introducing SBU-WSD-Corpus, as the first standard test set for the Persian All-words WSD task. SBU-WSD-Corpus is manually annotated with senses from the Persian WordNet (FarsNet) sense inventory. To this end, three annotators used SAMP (a tool for sense annotation based on FarsNet lexical graph) to perform the annotation task. SBU-WSD-Corpus consists of 19 Persian documents in different domains such as Sports, Science, Arts, etc. It includes 5892 content words of Persian running text and 3371 manually sense annotated words (2073 nouns, 566 verbs, 610 adjectives, and 122 adverbs). Providing baselines for future studies on the Persian All-words WSD task, we evaluate several WSD models on SBU-WSD-Corpus. |
| format | Article |
| id | doaj-art-ad599d0100b34b9f8df68986f8b1316e |
| institution | Kabale University |
| issn | 2645-4343 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | University of science and culture |
| record_format | Article |
| series | International Journal of Web Research |
| spelling | doaj-art-ad599d0100b34b9f8df68986f8b1316e2025-01-04T10:24:02ZengUniversity of science and cultureInternational Journal of Web Research2645-43432022-07-0152778510.22133/ijwr.2023.354098.1128SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense DisambiguationHossein Rouhizadeh0Mehrnoush Shamsfard1https://orcid.org/0000-0002-7027-7529Vahide Tajalli 2Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, IranUniversity of Tehran, Tehran, IranWord Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context. Developing standard WSD test collections can be mentioned as an important prerequisite for developing and evaluating different WSD systems in the language of interest. Although many WSD test collections have been developed for a variety of languages, no standard All-words WSD benchmark is available for Persian. In this paper, we address this shortage for the Persian language by introducing SBU-WSD-Corpus, as the first standard test set for the Persian All-words WSD task. SBU-WSD-Corpus is manually annotated with senses from the Persian WordNet (FarsNet) sense inventory. To this end, three annotators used SAMP (a tool for sense annotation based on FarsNet lexical graph) to perform the annotation task. SBU-WSD-Corpus consists of 19 Persian documents in different domains such as Sports, Science, Arts, etc. It includes 5892 content words of Persian running text and 3371 manually sense annotated words (2073 nouns, 566 verbs, 610 adjectives, and 122 adverbs). Providing baselines for future studies on the Persian All-words WSD task, we evaluate several WSD models on SBU-WSD-Corpus. https://ijwr.usc.ac.ir/article_165861_444adb5f7ab0eada122fc44b4722aef8.pdfword sense disambiguationwsd corpusall-words wsdpersian language processing |
| spellingShingle | Hossein Rouhizadeh Mehrnoush Shamsfard Vahide Tajalli SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation International Journal of Web Research word sense disambiguation wsd corpus all-words wsd persian language processing |
| title | SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation |
| title_full | SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation |
| title_fullStr | SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation |
| title_full_unstemmed | SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation |
| title_short | SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation |
| title_sort | sbu wsd corpus a sense annotated corpus for persian all words word sense disambiguation |
| topic | word sense disambiguation wsd corpus all-words wsd persian language processing |
| url | https://ijwr.usc.ac.ir/article_165861_444adb5f7ab0eada122fc44b4722aef8.pdf |
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