SemEval-2010 Task 1: Coreference Resolution in Multiple Languages
- Marta Recasens, Lluís Màrquez i Villodre, Yannick Versley
- Computer Science, LinguisticsInternational Workshop on Semantic Evaluation
- 4 June 2009
An insight is provided into (i) the portability of coreference resolution systems across languages, and (ii) the effect of different scoring metrics on ranking the output of the participant systems.
BART: A Modular Toolkit for Coreference Resolution
- Yannick Versley, Simone Paolo Ponzetto, Alessandro Moschitti
- Computer ScienceAnnual Meeting of the Association for…
- 1 May 2008
B BART is presented, a highly modular toolkit for developing coreference applications that was used to extend a reimplementation of the Soon et al. (2001) proposal with a variety of additional syntactic and knowledge-based features, and experiment with alternative resolution processes, preprocessing tools, and classifiers.
Overview of the SPMRL 2013 Shared Task: A Cross-Framework Evaluation of Parsing Morphologically Rich Languages
- Djamé Seddah, Reut Tsarfaty, Eric Villemonte de la Clergerie
- Computer ScienceSPMRL@EMNLP
- 18 October 2013
This paper presents and analyzes parsing results obtained by the task participants, and provides an analysis and comparison of the parsers across languages and frameworks, reported for gold input as well as more realistic parsing scenarios.
Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither
- Reut Tsarfaty, Djamé Seddah, L. Tounsi
- Computer Science, LinguisticsSPMRL@NAACL-HLT
- 5 June 2010
This paper synthesizes the contributions of researchers working on parsing Arabic, Basque, French, German, Hebrew, Hindi and Korean to point out shared solutions across languages and suggests itself as a source of directions for future investigations.
Pronoun-Focused MT and Cross-Lingual Pronoun Prediction: Findings of the 2015 DiscoMT Shared Task on Pronoun Translation
- Christian Hardmeier, Preslav Nakov, Sara Stymne, J. Tiedemann, Yannick Versley, M. Cettolo
- Linguistics, PsychologyDiscoMT@EMNLP
- 1 September 2015
We describe the design, the evaluation setup, and the results of the DiscoMT 2015 shared task, which included two subtasks, relevant to both the machine translation (MT) and the discourse…
Anaphora Resolution: Algorithms, Resources, and Applications
- Massimo Poesio, Roland Stuckardt, Yannick Versley
- Computer Science
- 5 August 2016
This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to todays state-of-the-art approaches, which use advanced…
Parser evaluation across Text Types
- Yannick Versley
- Computer Science
- 2005
It is found that a parser trained on the WSJ portion of the Penn Treebank performs less well on the Brown corpus (the subset that is available in the PTB bracketing format) than a parser that has been trained only on theBrown corpus, although the latter one has only half as many sentences as the former.
Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction
- Liane Guillou, Christian Hardmeier, Andrei Popescu-Belis
- Psychology, LinguisticsConference on Machine Translation
- 27 November 2019
We describe the design, the evaluation setup, and the results of the 2016 WMT shared task on cross-lingual pronoun prediction. This is a classification task in which participants are asked to provi…
Anaphoric Annotation of Wikipedia and Blogs in the Live Memories Corpus
- K. Rodríguez, F. Delogu, Yannick Versley, Egon W. Stemle, Massimo Poesio
- LinguisticsInternational Conference on Language Resources…
- 1 May 2010
The Live Memories corpus is an Italian corpus annotated for anaphoric relations that contains texts from the Italian Wikipedia about the region Trentino/Sud Tirol and from blog sites with users' comments.
BART: A Multilingual Anaphora Resolution System
- Samuel Broscheit, Massimo Poesio, Roberto Zanoli
- Computer ScienceInternational Workshop on Semantic Evaluation
- 15 July 2010
BART is a highly modular toolkit for coreference resolution that supports state-of-the-art statistical approaches and enables efficient feature engineering and relies on a maximum entropy-based classifier for pairs of mentions.
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