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3 results on '"Cherifa Ben Khelil"'

2. PARSEME corpus release 1.3

Author

Agata, Savary, Cherifa Ben Khelil, Carlos, Ramisch, Voula, Giouli, Verginica Barbu Mititelu, Najet Hadj Mohamed, Cvetana, Krstev, Chaya, Liebeskind, Hongzhi, Xu, Sara, Stymne, Tunga, Güngör, Thomas, Pickard, Bruno, Guillaume, Eduard, Bejček, Archna, Bhatia, Marie, Candito, Polona, Gantar, Uxoa, Iñurrieta, Albert, Gatt, Jolanta, Kovalevskaite, Timm, Lichte, Nikola, Ljubešić, Monti, Johanna, Carla Parra Escartín, Mehrnoush, Shamsfard, Ivelina, Stoyanova, Veronika, Vincze, and Abigail, Walsh

Subjects
we introduce gENder-IT, especially for sentence-level MT systems. The identification of ambiguity and its subsequent resolution is a challenging task for which currently there aren’t any specific resources or challenge sets available. In this paper, where needed, on the Italian target side, Languages differ in terms of the absence or presence of gender features, Languages differ in terms of the absence or presence of gender features, the number of gender classes and whether and where gender features are explicitly marked. These cross-linguistic differences can lead to ambiguities that are difficult to resolve, especially for sentence-level MT systems. The identification of ambiguity and its subsequent resolution is a challenging task for which currently there aren’t any specific resources or challenge sets available. In this paper, we introduce gENder-IT, an English–Italian challenge set focusing on the resolution of natural gender phenomena by providing word-level gender tags on the English source side and multiple gender alternative translations, where needed, on the Italian target side, the number of gender classes and whether and where gender features are explicitly marked. These cross-linguistic differences can lead to ambiguities that are difficult to resolve, an English–Italian challenge set focusing on the resolution of natural gender phenomena by providing word-level gender tags on the English source side and multiple gender alternative translations
Published
2023

3. Generating Arabic TAG for syntax-semantics analysis

Author

Cherifa Ben Khelil, Chiraz Ben Othmane Zribi, Denys Duchier, Yannick Parmentier, Laboratoire d'Informatique Fondamentale d'Orléans (LIFO), Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Laboratoire d'Informatique Fondamentale et Appliquée de Tours (LIFAT), Université de Tours (UT)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), École Nationale des Sciences de l'Informatique [Manouba] (ENSI), Université de la Manouba [Tunisie] (UMA), Natural Language Processing : representations, inference and semantics (SYNALP), Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Linguistics and Language, Artificial Intelligence, Language and Linguistics, Software, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract

Preview available at https://www.cambridge.org/core/journals/natural-language-engineering/firstview; International audience; Arabic presents many challenges for automatic processing. Although several research studies have addressed some issues, electronic resources for processing Arabic remain relatively rare or not widely available. In this paper, we propose a Tree-adjoining grammar with a syntax-semantic interface. It is applied to the modern standard Arabic, but it can be easily adapted to other languages. This grammar named ArabTAG V2.0 (Arabic Tree Adjoining Grammar) is semi-automatically generated by means of an abstract representation called meta-grammar. To ensure its development, ArabTAG V2.0 benefits from a grammar testing environment that uses a corpus of phenomena. Further experiments were performed to check the coverage of this grammar as well as the syntax-semantic analysis. The results showed that ArabTAG V2.0 can cover the majority of syntactical structures and different linguistic phenomena with a precision rate of 88.76%. Moreover, we were able to semantically analyze sentences and build their semantic representations with a precision rate of about 95.63%.

Published
2022
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