Kuznetsov, Ilia ; Gurevych, Iryna (2024)
An Inclusive Notion of Text.
The 61st Annual Meeting of the Association for Computational Linguistics. Toronto, Canada (09.-14.07.2023)
doi: 10.26083/tuprints-00027658
Konferenzveröffentlichung, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
Natural language processing (NLP) researchers develop models of grammar, meaning and communication based on written text. Due to task and data differences, what is considered text can vary substantially across studies. A conceptual framework for systematically capturing these differences is lacking. We argue that clarity on the notion of text is crucial for reproducible and generalizable NLP. Towards that goal, we propose common terminology to discuss the production and transformation of textual data, and introduce a two-tier taxonomy of linguistic and non-linguistic elements that are available in textual sources and can be used in NLP modeling. We apply this taxonomy to survey existing work that extends the notion of text beyond the conservative language-centered view. We outline key desiderata and challenges of the emerging inclusive approach to text in NLP, and suggest community-level reporting as a crucial next step to consolidate the discussion.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Kuznetsov, Ilia ; Gurevych, Iryna |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | An Inclusive Notion of Text |
| Sprache: | Englisch |
| Publikationsjahr: | 8 Juli 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2023 |
| Ort der Erstveröffentlichung: | Kerrville, TX, USA |
| Verlag: | ACL |
| Buchtitel: | Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) |
| Veranstaltungstitel: | The 61st Annual Meeting of the Association for Computational Linguistics |
| Veranstaltungsort: | Toronto, Canada |
| Veranstaltungsdatum: | 09.-14.07.2023 |
| DOI: | 10.26083/tuprints-00027658 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/27658 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Natural language processing (NLP) researchers develop models of grammar, meaning and communication based on written text. Due to task and data differences, what is considered text can vary substantially across studies. A conceptual framework for systematically capturing these differences is lacking. We argue that clarity on the notion of text is crucial for reproducible and generalizable NLP. Towards that goal, we propose common terminology to discuss the production and transformation of textual data, and introduce a two-tier taxonomy of linguistic and non-linguistic elements that are available in textual sources and can be used in NLP modeling. We apply this taxonomy to survey existing work that extends the notion of text beyond the conservative language-centered view. We outline key desiderata and challenges of the emerging inclusive approach to text in NLP, and suggest community-level reporting as a crucial next step to consolidate the discussion. |
| ID-Nummer: | 2023.acl-long.633 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-276586 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung |
| Hinterlegungsdatum: | 08 Jul 2024 09:23 |
| Letzte Änderung: | 09 Jul 2024 09:23 |
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| Suche nach Titel in: | TUfind oder in Google |
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