{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cogalex-2-0-impact-of-data-quality-on-lexical","title":"CogALex 2.0: Impact of Data Quality on Lexical-Semantic Relation Prediction","arxiv_id":null,"date":"2021-12-14","proceeding":"NeurIPS Data-Centric AI Workshop 2021 12","authors":["Christian Lang","Lennart Wachowiak","Barbara Heinisch","Dagmar Gromann"],"abstract":"Predicting lexical-semantic relations between word pairs has successfully been accomplished by pre-trained neural language models. An XLM-RoBERTa-based approach, for instance, achieved the best performance differentiating between hypernymy, synonymy, antonymy, and random relations in four languages in the CogALex-VI 2020 shared task. However, the results also revealed strong performance divergences between languages and confusions of specific relations, especially hypernymy and synonymy. Upon inspection, a difference in data quality across languages and relations could be observed. Thus, we provide a manually improved dataset for lexical-semantic relation prediction and evaluate its impact across three pre-trained neural language models.","url_abs":"https://datacentricai.org/papers/164_CameraReady_CogALex_2_0.pdf","url_pdf":"https://datacentricai.org/papers/164_CameraReady_CogALex_2_0.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"cogalex-2-0-impact-of-data-quality-on-lexical","repo_url":"https://github.com/Text2TCS/CogALex-2.0","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"hypernym-discovery","task_name":"Hypernym Discovery"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-classification","task_name":"Relation Classification"},{"task_slug":"relation-prediction","task_name":"Relation Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}