Marie Dubremetz

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We propose an approach to detecting the rhetorical figure called chiasmus, which involves the repetition of a pair of words in reverse order, as in “all for one, one for all”. Although repetitions of words are common in natural language, true instances of chiasmus are rare, and the question is therefore whether a computer can effectively distinguish a(More)
RÉSUMÉ Cette recherche porte sur le chiasme de mots : figure de style jouant sur la réversion (ex. « Bonnet blanc, blanc bonnet »). Elle place le chiasme dans la problématique de sa reconnaissance automatique : qu’est-ce qui le définit et comment un ordinateur peut le trouver ? Nous apportons une description formelle du phénomène. Puis nous procédons à la(More)
The chiasmus is a rhetorical figure involving the repetition of a pair of words in reverse order, as in “all for one, one for all”. Previous work on detecting chiasmus in running text has only considered superficial features like words and punctuation. In this paper, we explore the use of syntactic features as a means to improve the quality of chiasmus(More)
Our project is based on the theme of Multi Word Expressions (MWE) we will focus on the problem of extraction. This task is important for improving lexical resources used for tasks such as tokenization, parsing or translation. In our study we will work on a French corpus. Our aim will be to not only select but also validate automatically which candidates are(More)
Figurative language identification is a hard problem for computers. In this paper we handle a subproblem: chiasmus detection. By chiasmus we understand a rhetorical figure that consists in repeating two elements in reverse order: “First shall be last, last shall be first”. Chiasmus detection is a needle-in-the-haystack problem with a couple of true(More)
Extraction and validation of multiword expressions (MWEs) thanks to association measures is a very common method. Researchers use it for extraction of MWEs of different lengths or different syntactic structures. However, we never wonder if the association measures collected on an MWE with one particular structure (e.g. Verb-Preposition) is relevant for(More)
Mutlti Word Epressions (MWE) are an important problem in NLP. Many researchers use association measures for collecting and evaluating MWE candidates. In this paper we propose to check if it is legitimate to use those measures when data are only collected on one pattern of MWE (e.g. NounAdjective) for evaluating candidates belonging to an other pattern (e.g.(More)
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