Pere Comas

Also published as: Pere R. Comas


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TweetNorm_es: an annotated corpus for Spanish microtext normalization
Iñaki Alegria | Nora Aranberri | Pere Comas | Víctor Fresno | Pablo Gamallo | Lluis Padró | Iñaki San Vicente | Jordi Turmo | Arkaitz Zubiaga
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this paper we introduce TweetNorm_es, an annotated corpus of tweets in Spanish language, which we make publicly available under the terms of the CC-BY license. This corpus is intended for development and testing of microtext normalization systems. It was created for Tweet-Norm, a tweet normalization workshop and shared task, and is the result of a joint annotation effort from different research groups. In this paper we describe the methodology defined to build the corpus as well as the guidelines followed in the annotation process. We also present a brief overview of the Tweet-Norm shared task, as the first evaluation environment where the corpus was used.


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Full Machine Translation for Factoid Question Answering
Cristina España-Bonet | Pere R. Comas
Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)


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Evaluation Protocol and Tools for Question-Answering on Speech Transcripts
Nicolas Moreau | Olivier Hamon | Djamel Mostefa | Sophie Rosset | Olivier Galibert | Lori Lamel | Jordi Turmo | Pere R. Comas | Paolo Rosso | Davide Buscaldi | Khalid Choukri
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Question Answering (QA) technology aims at providing relevant answers to natural language questions. Most Question Answering research has focused on mining document collections containing written texts to answer written questions. In addition to written sources, a large (and growing) amount of potentially interesting information appears in spoken documents, such as broadcast news, speeches, seminars, meetings or telephone conversations. The QAST track (Question-Answering on Speech Transcripts) was introduced in CLEF to investigate the problem of question answering in such audio documents. This paper describes in detail the evaluation protocol and tools designed and developed for the CLEF-QAST evaluation campaigns that have taken place between 2007 and 2009. We first remind the data, question sets, and submission procedures that were produced or set up during these three campaigns. As for the evaluation procedure, the interface that was developed to ease the assessors’ work is described. In addition, this paper introduces a methodology for a semi-automatic evaluation of QAST systems based on time slot comparisons. Finally, the QAST Evaluation Package 2007-2009 resulting from these evaluation campaigns is also introduced.


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Question Answering on Speech Transcriptions: the QAST evaluation in CLEF
Lori Lamel | Sophie Rosset | Christelle Ayache | Djamel Mostefa | Jordi Turmo | Pere Comas
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper reports on the QAST track of CLEF aiming to evaluate Question Answering on Speech Transcriptions. Accessing information in spoken documents provides additional challenges to those of text-based QA, needing to address the characteristics of spoken language, as well as errors in the case of automatic transcriptions of spontaneous speech. The framework and results of the pilot QAst evaluation held as part of CLEF 2007 is described, illustrating some of the additional challenges posed by QA in spoken documents relative to written ones. The current plans for future multiple-language and multiple-task QAst evaluations are described.


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A Robust Combination Strategy for Semantic Role Labeling
Lluís Màrquez | Mihai Surdeanu | Pere Comas | Jordi Turmo
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

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Semantic Role Labeling as Sequential Tagging
Lluís Màrquez | Pere Comas | Jesús Giménez | Neus Català
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)