Papers by Lucie Barque
FrSemCor: Annotating a French Corpus with Supersenses (2020.lrec-1)
Copied to clipboard
Lucie Barque, Pauline Haas, Richard Huyghe, Delphine Tribout, Marie Candito, Benoit Crabbé, Vincent Segonne
| Challenge: | a new project aims to provide a sense-annotated corpus of French for NLP and linguistics research . the project uses WordNet Unique Beginners as semantic tags to provide interoperability . |
| Approach: | They propose to use WordNet Unique Beginners as semantic tags to annotate French nouns . the project aims to provide a gold standard resource for linguistics and linguistic research . |
| Outcome: | The proposed resource is released online under a Creative Commons license. |
SLICE: Supersense-based Lightweight Interpretable Contextual Embeddings (2020.coling-main)
Copied to clipboard
| Challenge: | Contextualised embeddings are a key component of human languages but their opaqueness makes it difficult to interpret their behaviour. |
| Approach: | They propose a weakly supervised method to learn interpretable embeddings from raw corpora and seed words. |
| Outcome: | The proposed model can represent both a word and its context as embeddings into the same compact space, whose dimensions correspond to interpretable supersenses. |
Annotating the French Wiktionary with supersenses for large scale lexical analysis: a use case to assess form-meaning relationships within the nominal lexicon (2025.coling-main)
Copied to clipboard
| Challenge: | Conducting large-scale empirical studies in lexical semantics remains an elusive goal for many languages lacking comprehensive semantic resources. |
| Approach: | They propose to use the Princeton WordNet to enrich the French Wiktionary with general semantic classes, known as supersenses, using a limited amount of manually annotated data. |
| Outcome: | The proposed method can be extended to other languages provided an electronic lexicon and manually annotated senses are available. |