International audienceWe 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 Corefer-ence 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
We report here on a study of interannotator agreement in the coreference task as defined by the Mess...
Anaphora resolution is the key task for some of the Natural Language Processing (NLP) tasks like the...
The task of coreference resolution has attracted a great deal of attention in the literature due to ...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
We present CROC (Coreference Resolution for Oral Corpus), the first machine learning system for core...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
International audienceThis article presents ANCOR_Centre, a French coreference corpus, available und...
International audienceWe propose an end-to-end coreference resolution system obtained by adapting ne...
National audienceMention-pair classification for corefence resolution on spontaneous spoken French. ...
International audienceNotre objectif est l'élaboration d'un système de détection automatique de rela...
International audienceThis paper presents a corpus-based analysis of coreference and anaphoric relat...
We present in this paper the coreference mechanism implemented in the M-LaSIE system, a prototype mu...
This paper presents C-PROM, an annotated corpus for French prominence studies. The corpus, including...
Abstract. The majority of current coreference resolution systems rely on annotated corpora to train ...
We report here on a study of interannotator agreement in the coreference task as defined by the Mess...
Anaphora resolution is the key task for some of the Natural Language Processing (NLP) tasks like the...
The task of coreference resolution has attracted a great deal of attention in the literature due to ...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
We present CROC (Coreference Resolution for Oral Corpus), the first machine learning system for core...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
International audienceWe present CROC (Coreference Resolution for Oral Corpus), the first machine le...
International audienceThis article presents ANCOR_Centre, a French coreference corpus, available und...
International audienceWe propose an end-to-end coreference resolution system obtained by adapting ne...
National audienceMention-pair classification for corefence resolution on spontaneous spoken French. ...
International audienceNotre objectif est l'élaboration d'un système de détection automatique de rela...
International audienceThis paper presents a corpus-based analysis of coreference and anaphoric relat...
We present in this paper the coreference mechanism implemented in the M-LaSIE system, a prototype mu...
This paper presents C-PROM, an annotated corpus for French prominence studies. The corpus, including...
Abstract. The majority of current coreference resolution systems rely on annotated corpora to train ...
We report here on a study of interannotator agreement in the coreference task as defined by the Mess...
Anaphora resolution is the key task for some of the Natural Language Processing (NLP) tasks like the...
The task of coreference resolution has attracted a great deal of attention in the literature due to ...