Projets par an
Résumé
Current Abstract Meaning Representation (AMR) annotation guidelines, which largely tie argument structure to lexical rolesets, systematically misrepresent cases in which key semantic roles stem from clause-level structure rather than the verb, leaving these meanings either unnaturally attached, incorrect, or unexpressed. To address this limitation, we present CxGr-AMR, a novel extension of AMR that captures the semantics of various types of phrasal constructions, including argument structure constructions. We first examine how such cases are handled under current Standard-AMR guidelines and show that these analyses are often inadequate when constructionally contributed roles clash with those assigned by the verb. We then provide a theoretical grounding for our CxGr-AMR rolesets that lay out the relationship between the syntactic signatures of constructional slots and particular semantic roles associated with them. Finally, we develop an annotation-expert-in-the loop pipeline for the semi-automatic annotation of sentences, and release a dataset containing 355 instances of phrasal constructions annotated with both Standard and CxGr-AMR.
| langue originale | Anglais |
|---|---|
| Pages | 1--19 |
| Etat de la publication | Publié - 2026 |
| Evénement | The Seventh International Workshop on Designing Meaning Representations - Palma de Mallorca, Espagne Durée: 11 mai 2026 → … https://dmr2026.github.io |
Colloque
| Colloque | The Seventh International Workshop on Designing Meaning Representations |
|---|---|
| Titre abrégé | DMR 2026 |
| Pays/Territoire | Espagne |
| La ville | Palma de Mallorca |
| période | 11/05/26 → … |
| Adresse Internet |
Empreinte digitale
Examiner les sujets de recherche de « CxGr-AMR: Extending Abstract Meaning Representation Beyond Lexically Anchored Relations with Constructional Rolesets ». Ensemble, ils forment une empreinte digitale unique.Projets
- 2 Actif
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CxG-LEARN: Opérateurs syntactico-semantiques pour l'apprentissage automatique de grammaires de construction basées sur l'usage
Beuls, K. (Responsable du Projet) & Van Eecke, P. (CoPI)
1/01/24 → 31/12/27
Projet: Recherche
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ARIAC by DigitalWallonia4.AI: Applications et Recherche pour une Intelligence Artificielle de Confiance (TRAIL-Foundations)
Frénay, B. (Responsable du Projet), Jacquet, J.-M. (Co-investigateur), Dumas, B. (Co-investigateur), Devroey, X. (Co-investigateur), Tuci, E. (Co-investigateur), Beuls, K. (Co-investigateur), Linden, I. (Co-investigateur), Burnay, C. (Co-investigateur), Vanderose, B. (Co-investigateur), Cleve, A. (Co-investigateur), Perrouin, G. (Co-investigateur), Heymans, P. (Co-investigateur), Vanhoof, W. (Co-investigateur), Ferry-Danini, J. (Co-investigateur) & Balfroid, M. (Chercheur)
1/01/21 → 30/09/27
Projet: Recherche
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