Coreference Resolution for French Oral Data: Machine Learning Experiments with ANCOR
| Autor: | Jean-Yves Antoine, Adèle Désoyer, Anaïs Lefeuvre, Frédéric Landragin, Isabelle Tellier, Marco Dinarelli |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Coreference
Relation (database) business.industry Computer science Anaphora (linguistics) 02 engineering and technology Resolution (logic) Machine learning computer.software_genre Set (abstract data type) 020204 information systems ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer Natural language processing |
| Zdroj: | Computational Linguistics and Intelligent Text Processing ISBN: 9783319754765 CICLing (1) |
| DOI: | 10.1007/978-3-319-75477-2_36 |
| Popis: | We present CROC (Coreference Resolution for Oral Corpus), the first machine learning system for coreference resolution in French. One specific aspect of the system is that it has been trained on data that come exclusively from transcribed speech, namely ANCOR (ANaphora and Coreference in ORal corpus), the first large-scale French corpus with anaphorical relation annotations. In its current state, the CROC system requires pre-annotated mentions. We detail the features used for the learning algorithms, and we present a set of experiments with these features. The scores we obtain are close to those of state-of-the-art systems for written English. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|