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Résumé
This paper introduces a novel methodology for extracting semantic frames from text corpora. Building on recent advances in computational construction grammar, the method captures expert knowledge of how semantic frames can be expressed in the form of conventionalised form-meaning pairings, called constructions. By combining these constructions in a semantic parsing process, the frame-semantic structure of a sentence is retrieved through the intermediary of its morpho-syntactic structure. The main advantage of this approach is that state-of-the-art results are achieved, without the need for annotated training data. We demonstrate the method in a case study where causation frames are extracted from English newspaper articles, and compare it to a commonly used approach based on Conditional Random Fields (CRFs). The computational construction grammar approach yields a word-level F 1 score of 78.5%, outperforming the CRF approach by 4.5 percentage points.
langue originale | Anglais |
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Numéro d'article | 20180015 |
Pages (de - à) | 20180015 |
Nombre de pages | 1 |
journal | Linguistics Vanguard |
Volume | 7 |
Numéro de publication | 1 |
Les DOIs | |
Etat de la publication | Publié - 2021 |
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Meaning and understanding in human-centric AI
Beuls, K. (Responsable du Projet)
1/10/20 → 30/09/24
Projet: Recherche