Conference
French coreference for spoken and written language
| العنوان: | French coreference for spoken and written language |
|---|---|
| المؤلفون: | Wilkens, Rodrigo, Oberle, Bruno, Landragin, Frédéric, Todirascu, Amalia |
| المساهمون: | Informatics Institute = Instituto de Informática Porto Alegre, Universidade Federal do Rio Grande do Sul Porto Alegre (UFRGS), Linguistique, Langues et Parole (LILPA), Université de Strasbourg (UNISTRA), Lattice - Langues, Textes, Traitements informatiques, Cognition - UMR 8094 (Lattice), Université Sorbonne Nouvelle - Paris 3-Université Sorbonne Paris Cité (USPC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Sciences et Lettres (PSL)-Département Littératures et langage - ENS-PSL (LILA), École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL), ANR-16-CE28-0005,ALECTOR,Aide à la LECTure pour améliORer l'accès aux documents pour enfants dyslexiques(2016), ANR-15-CE38-0008,DEMOCRAT,DEscription et MOdélisation des Chaînes de Référence : outils pour l'Annotation de corpus (en diachronie et en langues comparées) et le Traitement automatique(2015) |
| المصدر: | Language Resources and Evaluation Conference (LREC 2020) ; https://hal.science/hal-02476902 ; Language Resources and Evaluation Conference (LREC 2020), 2020, Marseille, France. pp.80-89 ; https://www.aclweb.org/anthology/2020.lrec-1.10 |
| بيانات النشر: | CCSD |
| سنة النشر: | 2020 |
| المجموعة: | Université Sorbonne Nouvelle - Paris 3: HAL |
| مصطلحات موضوعية: | Coreference chains, Coreference Resolution, Evaluation, Anaphora, Automatic coreference resolution, Coreference, French language, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing |
| جغرافية الموضوع: | Marseille, France |
| الوصف: | International audience ; Coreference resolution aims at identifying and grouping all mentions referring to the same entity. In French, most systems run different setups, making their comparison difficult. In this paper, we present an extensive comparison of several coreference resolution systems for French. The systems have been trained on two corpora (ANCOR for spoken language and Democrat for written language) annotated with coreference chains, and augmented with syntactic and semantic information. The models are compared with different configurations (e.g. with and without singletons). In addition, we evaluate mention detection and coreference resolution apart. We present a full-stack model that outperforms the other approaches. This model allows us to study the impact of mention detection errors on coreference resolution. Our analysis shows that mention detection can be improved focusing on boundary identification while advances in the pronoun-noun relation detection can aid the coreference task. Another contribution of this work is the first end-to-end neural French coreference resolution model trained on Democrat (written texts), which compares to the state-of-the-art systems for oral French. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| الاتاحة: | https://hal.science/hal-02476902 https://hal.science/hal-02476902v1/document https://hal.science/hal-02476902v1/file/2020.lrec-1.10.pdf |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.A546D60B |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |