Marianne Djemaa


2016

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Corpus Annotation within the French FrameNet: a Domain-by-domain Methodology
Marianne Djemaa | Marie Candito | Philippe Muller | Laure Vieu
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper reports on the development of a French FrameNet, within the ASFALDA project. While the first phase of the project focused on the development of a French set of frames and corresponding lexicon (Candito et al., 2014), this paper concentrates on the subsequent corpus annotation phase, which focused on four notional domains (commercial transactions, cognitive stances, causality and verbal communication). Given full coverage is not reachable for a relatively “new” FrameNet project, we advocate that focusing on specific notional domains allowed us to obtain full lexical coverage for the frames of these domains, while partially reflecting word sense ambiguities. Furthermore, as frames and roles were annotated on two French Treebanks (the French Treebank (Abeillé and Barrier, 2004) and the Sequoia Treebank (Candito and Seddah, 2012), we were able to extract a syntactico-semantic lexicon from the annotated frames. In the resource’s current status, there are 98 frames, 662 frame evoking words, 872 senses, and about 13000 annotated frames, with their semantic roles assigned to portions of text. The French FrameNet is freely available at alpage.inria.fr/asfalda.

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A General Framework for the Annotation of Causality Based on FrameNet
Laure Vieu | Philippe Muller | Marie Candito | Marianne Djemaa
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We present here a general set of semantic frames to annotate causal expressions, with a rich lexicon in French and an annotated corpus of about 5000 instances of causal lexical items with their corresponding semantic frames. The aim of our project is to have both the largest possible coverage of causal phenomena in French, across all parts of speech, and have it linked to a general semantic framework such as FN, to benefit in particular from the relations between other semantic frames, e.g., temporal ones or intentional ones, and the underlying upper lexical ontology that enable some forms of reasoning. This is part of the larger ASFALDA French FrameNet project, which focuses on a few different notional domains which are interesting in their own right (Djemma et al., 2016), including cognitive positions and communication frames. In the process of building the French lexicon and preparing the annotation of the corpus, we had to remodel some of the frames proposed in FN based on English data, with hopefully more precise frame definitions to facilitate human annotation. This includes semantic clarifications of frames and frame elements, redundancy elimination, and added coverage. The result is arguably a significant improvement of the treatment of causality in FN itself.

2014

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Addressing object predicative complements in a French FrameNet (Traitement FrameNet des constructions à attribut de l’objet) [in French]
Marianne Djemaa
Proceedings of TALN 2014 (Volume 4: RECITAL - Student Research Workshop)

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Developing a French FrameNet: Methodology and First results
Marie Candito | Pascal Amsili | Lucie Barque | Farah Benamara | Gaël de Chalendar | Marianne Djemaa | Pauline Haas | Richard Huyghe | Yvette Yannick Mathieu | Philippe Muller | Benoît Sagot | Laure Vieu
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The Asfalda project aims to develop a French corpus with frame-based semantic annotations and automatic tools for shallow semantic analysis. We present the first part of the project: focusing on a set of notional domains, we delimited a subset of English frames, adapted them to French data when necessary, and developed the corresponding French lexicon. We believe that working domain by domain helped us to enforce the coherence of the resulting resource, and also has the advantage that, though the number of frames is limited (around a hundred), we obtain full coverage within a given domain.