Joan Codina-Filba

Also published as: Joan Codina, Joan Codina-Filbà


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Towards Multiple Antecedent Coreference Resolution in Specialized Discourse
Alicia Burga | Sergio Cajal | Joan Codina-Filbà | Leo Wanner
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Despite the popularity of coreference resolution as a research topic, the overwhelming majority of the work in this area focused so far on single antecedence coreference only. Multiple antecedent coreference (MAC) has been largely neglected. This can be explained by the scarcity of the phenomenon of MAC in generic discourse. However, in specialized discourse such as patents, MAC is very dominant. It seems thus unavoidable to address the problem of MAC resolution in the context of tasks related to automatic patent material processing, among them abstractive summarization, deep parsing of patents, construction of concept maps of the inventions, etc. We present the first version of an operational rule-based MAC resolution strategy for patent material that covers the three major types of MAC: (i) nominal MAC, (ii) MAC with personal / relative pronouns, and MAC with reflexive / reciprocal pronouns. The evaluation shows that our strategy performs well in terms of precision and recall.

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Praat on the Web: An Upgrade of Praat for Semi-Automatic Speech Annotation
Mónica Domínguez | Iván Latorre | Mireia Farrús | Joan Codina-Filbà | Leo Wanner
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations

This paper presents an implementation of the widely used speech analysis tool Praat as a web application with an extended functionality for feature annotation. In particular, Praat on the Web addresses some of the central limitations of the original Praat tool and provides (i) enhanced visualization of annotations in a dedicated window for feature annotation at interval and point segments, (ii) a dynamic scripting composition exemplified with a modular prosody tagger, and (iii) portability and an operational web interface. Speech annotation tools with such a functionality are key for exploring large corpora and designing modular pipelines.


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Improving Collocation Correction by Ranking Suggestions Using Linguistic Knowledge
Roberto Carlini | Joan Codina-Filba | Leo Wanner
Proceedings of the third workshop on NLP for computer-assisted language learning

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An Exercise in Reuse of Resources: Adapting General Discourse Coreference Resolution for Detecting Lexical Chains in Patent Documentation
Nadjet Bouayad-Agha | Alicia Burga | Gerard Casamayor | Joan Codina | Rogelio Nazar | Leo Wanner
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The Stanford Coreference Resolution System (StCR) is a multi-pass, rule-based system that scored best in the CoNLL 2011 shared task on general discourse coreference resolution. We describe how the StCR has been adapted to the specific domain of patents and give some cues on how it can be adapted to other domains. We present a linguistic analysis of the patent domain and how we were able to adapt the rules to the domain and to expand coreferences with some lexical chains. A comparative evaluation shows an improvement of the coreference resolution system, denoting that (i) StCR is a valuable tool across different text genres; (ii) specialized discourse NLP may significantly benefit from general discourse NLP research.


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FBM: Combining lexicon-based ML and heuristics for Social Media Polarities
Carlos Rodríguez-Penagos | Jordi Atserias Batalla | Joan Codina-Filbà | David García-Narbona | Jens Grivolla | Patrik Lambert | Roser Saurí
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)


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A Hybrid Framework for Scalable Opinion Mining in Social Media: Detecting Polarities and Attitude Targets
Carlos Rodríguez-Penagos | Jens Grivolla | Joan Codina-Filba
Proceedings of the Workshop on Semantic Analysis in Social Media


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Opinion Mining of Spanish Customer Comments with Non-Expert Annotations on Mechanical Turk
Bart Mellebeek | Francesc Benavent | Jens Grivolla | Joan Codina | Marta R. Costa-jussà | Rafael Banchs
Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk