Clément Plancq


pdf bib
Sonnet Combinatorics with OuPoCo
Thierry Poibeau | Mylène Maignant | Frédérique Mélanie-Becquet | Clément Plancq | Matthieu Raffard | Mathilde Roussel
Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

In this paper, we describe OuPoCo, a system producing new sonnets by recombining verses from existing sonnets, following an idea that Queneau described in his book “Cent Mille Milliards de poèmes, Gallimard”, 1961. We propose to demonstrate different outputs of our implementation (a Web site, a Twitter bot and a specifically developed device, called ‘La Boîte à poésie’) based on a corpus of 19th century French poetry. Our goal is to make people interested in poetry again, by giving access to automatically produced sonnets through original and entertaining channels and devices.


pdf bib
Un étiqueteur en ligne du Français (An online tagger for French)
Yoann Dupont | Clément Plancq
Actes des 24ème Conférence sur le Traitement Automatique des Langues Naturelles. Volume 3 - Démonstrations

Nous proposons ici une interface en ligne pour étiqueter des textes en français selon trois niveaux d’analyses : la morphosyntaxe, le chunking et la reconnaissance des entités nommées. L’interface se veut simple et les étiquetages réutilisables, ces derniers pouvant être exportés en différents formats.


pdf bib
More than Word Cooccurrence: Exploring Support and Opposition in International Climate Negotiations with Semantic Parsing
Pablo Ruiz | Clément Plancq | Thierry Poibeau
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Text analysis methods widely used in digital humanities often involve word co-occurrence, e.g. concept co-occurrence networks. These methods provide a useful corpus overview, but cannot determine the predicates that relate co-occurring concepts. Our goal was identifying propositions expressing the points supported or opposed by participants in international climate negotiations. Word co-occurrence methods were not sufficient, and an analysis based on open relation extraction had limited coverage for nominal predicates. We present a pipeline which identifies the points that different actors support and oppose, via a domain model with support/opposition predicates, and analysis rules that exploit the output of semantic role labelling, syntactic dependencies and anaphora resolution. Entity linking and keyphrase extraction are also performed on the propositions related to each actor. A user interface allows examining the main concepts in points supported or opposed by each participant, which participants agree or disagree with each other, and about which issues. The system is an example of tools that digital humanities scholars are asking for, to render rich textual information (beyond word co-occurrence) more amenable to quantitative treatment. An evaluation of the tool was satisfactory.