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What Causes Unemployment? : Unsupervised Causality Mining from Swedish Governmental Reports
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- Dürlich, Luise (author)
- RISE,Uppsala universitet,Institutionen för lingvistik och filologi,RISE Research Institutes of Sweden, Kista, Sweden,Datavetenskap,Uppsala University, Sweden
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- Nivre, Joakim, 1962- (author)
- RISE,Uppsala universitet,Institutionen för lingvistik och filologi,RISE Research Institutes of Sweden, Kista, Sweden,Datavetenskap,Uppsala University, Sweden
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- Stymne, Sara, 1977- (author)
- Uppsala universitet,Institutionen för lingvistik och filologi,Uppsala University, Sweden
- (creator_code:org_t)
- Association for Computational Linguistics, 2023
- 2023
- English.
- In: Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023). - : Association for Computational Linguistics. - 9781959429739 ; , s. 25-29
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- Extracting statements about causality from text documents is a challenging task in the absence of annotated training data. We create a search system for causal statements about user-specified concepts by combining pattern matching of causal connectives with semantic similarity ranking, using a language model fine-tuned for semantic textual similarity. Preliminary experiments on a small test set from Swedish governmental reports show promising results in comparison to two simple baselines.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- causality mining
- unsupervised approaches
- Datorlingvistik
- Computational Linguistics
Publication and Content Type
- ref (subject category)
- kon (subject category)
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