Sérgio Curto
Also published as: Sergio Curto
2014
JUST.ASK, a QA system that learns to answer new questions from previous interactions
Sérgio Curto | Ana C. Mendes | Pedro Curto | Luísa Coheur | Ângela Costa
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Sérgio Curto | Ana C. Mendes | Pedro Curto | Luísa Coheur | Ângela Costa
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
We present JUST.ASK, a publicly available Question Answering system, which is freely available. Its architecture is composed of the usual Question Processing, Passage Retrieval and Answer Extraction components. Several details on the information generated and manipulated by each of these components are also provided to the user when interacting with the demonstration. Since JUST.ASK also learns to answer new questions based on users feedback, (s)he is invited to identify the correct answers. These will then be used to retrieve answers to future questions.
2013
Meet EDGAR, a tutoring agent at MONSERRATE
Pedro Fialho | Luísa Coheur | Sérgio Curto | Pedro Cláudio | Ângela Costa | Alberto Abad | Hugo Meinedo | Isabel Trancoso
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Pedro Fialho | Luísa Coheur | Sérgio Curto | Pedro Cláudio | Ângela Costa | Alberto Abad | Hugo Meinedo | Isabel Trancoso
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations
2012
Question Generation based on Lexico-Syntactic Patterns Learned from the Web
Sergio Curto | Ana Cristina Mendes | Luisa Coheur
Dialogue Discourse Volume 3
Sergio Curto | Ana Cristina Mendes | Luisa Coheur
Dialogue Discourse Volume 3
THE MENTOR automatically generates multiple-choice tests from a given text. This tool aims at supporting the dialogue system of the FalaComigo project, as one of FalaComigo’s goals is the interaction with tourists through questions/answers and quizzes about their visit. In a minimally supervised learning process and by leveraging the redundancy and linguistic variability of the Web, THE MENTOR learns lexico-syntactic patterns using a set of question/answer seeds. Afterward, these patterns are used to match the sentences from which new questions (and answers) can be generated. Finally, several ï¬lters are applied in order to discard low quality items. In this paper we detail the question generation task as performed by T- Mand evaluate its performance.
Extending a wordnet framework for simplicity and scalability
Pedro Fialho | Sérgio Curto | Ana Cristina Mendes | Luísa Coheur
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
Pedro Fialho | Sérgio Curto | Ana Cristina Mendes | Luísa Coheur
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
The WordNet knowledge model is currently implemented in multiple software frameworks providing procedural access to language instances of it. Frameworks tend to be focused on structural/design aspects of the model thus describing low level interfaces for linguistic knowledge retrieval. Typically the only high level feature directly accessible is word lookup while traversal of semantic relations leads to verbose/complex combinations of data structures, pointers and indexes which are irrelevant in an NLP context. Here is described an extension to the JWNL framework that hides technical requirements of access to WordNet features with an essentially word/sense based API applying terminology from the official online interface. This high level API is applied to the original English version of WordNet and to an SQL based Portuguese lexicon, translated into a WordNet based representation usable by JWNL.