Kepa Joseba Rodriguez

Also published as: Kepa J. Rodríguez, Kepa Joseba Rodríguez


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BART: A Multilingual Anaphora Resolution System
Samuel Broscheit | Massimo Poesio | Simone Paolo Ponzetto | Kepa Joseba Rodriguez | Lorenza Romano | Olga Uryupina | Yannick Versley | Roberto Zanoli
Proceedings of the 5th International Workshop on Semantic Evaluation

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Anaphoric Annotation of Wikipedia and Blogs in the Live Memories Corpus
Kepa Joseba Rodríguez | Francesca Delogu | Yannick Versley | Egon W. Stemle | Massimo Poesio
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The Live Memories corpus is an Italian corpus annotated for anaphoric relations. This annotation effort aims to contribute to two significant issues for the CL research: the lack of annotated anaphoric resources for Italian and the increasing interest for the social Web. The Live Memories Corpus contains texts from the Italian Wikipedia about the region Trentino/Süd Tirol and from blog sites with users' comments. It is planned to add a set of articles of local news papers. The corpus includes manual annotated information about morphosyntactic agreement, anaphoricity, and semantic class of the NPs. The anaphoric annotation includes discourse deixis, bridging relations and markes cases of ambiguity with the annotation of alternative interpretations. For the annotation of the anaphoric links the corpus takes into account specific phenomena of the Italian language like incorporated clitics and phonetically non realized pronouns. Reliability studies for the annotation of the mentioned phenomena and for annotation of anaphoric links in general offer satisfactory results. The Wikipedia and blogs dataset will be distributed under Creative Commons Attributions licence.


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Active Annotation in the LUNA Italian Corpus of Spontaneous Dialogues
Christian Raymond | Kepa Joseba Rodriguez | Giuseppe Riccardi
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In this paper we present an active approach to annotate with lexical and semantic labels an Italian corpus of conversational human-human and Wizard-of-Oz dialogues. This procedure consists in the use of a machine learner to assist human annotators in the labeling task. The computer assisted process engages human annotators to check and correct the automatic annotation rather than starting the annotation from un-annotated data. The active learning procedure is combined with an annotation error detection to control the reliablity of the annotation. With the goal of converging as fast as possible to reliable automatic annotations minimizing the human effort, we follow the active learning paradigm, which selects for annotation the most informative training examples required to achieve a better level of performance. We show that this procedure allows to quickly converge on correct annotations and thus minimize the cost of human supervision.


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Standoff Coordination for Multi-Tool Annotation in a Dialogue Corpus
Kepa Joseba Rodríguez | Stefanie Dipper | Michael Götze | Massimo Poesio | Giuseppe Riccardi | Christian Raymond | Joanna Rabiega-Wiśniewska
Proceedings of the Linguistic Annotation Workshop


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Producing Contextually Appropriate Intonation is an Information-State Based Dialogue System
Ivana Kruijff-Korbayova | Stina Ericsson | Kepa J. Rodríguez | Elena Karagjosova
10th Conference of the European Chapter of the Association for Computational Linguistics

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A dialogue system with contextually appropriate spoken output intonation
Ivana Kruijff-Korbayova | Elena Karagjosova | Kepa Joseba Rodriguez | Stina Ericsson