Montse Maritxalar

Also published as: M Maritxalar, M. Maritxalar


2020

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Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions
Andrea Horbach | Itziar Aldabe | Marie Bexte | Oier Lopez de Lacalle | Montse Maritxalar
Proceedings of the Twelfth Language Resources and Evaluation Conference

Automatic generation of reading comprehension questions is a topic receiving growing interest in the NLP community, but there is currently no consensus on evaluation metrics and many approaches focus on linguistic quality only while ignoring the pedagogic value and appropriateness of questions. This paper overcomes such weaknesses by a new evaluation scheme where questions from the questionnaire are structured in a hierarchical way to avoid confronting human annotators with evaluation measures that do not make sense for a certain question. We show through an annotation study that our scheme can be applied, but that expert annotators with some level of expertise are needed. We also created and evaluated two new evaluation data sets from the biology domain for Basque and German, composed of questions written by people with an educational background, which will be publicly released. Results show that manually generated questions are in general both of higher linguistic as well as pedagogic quality and that among the human generated questions, teacher-generated ones tend to be most useful.

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Domain Adapted Distant Supervision for Pedagogically Motivated Relation Extraction
Oscar Sainz | Oier Lopez de Lacalle | Itziar Aldabe | Montse Maritxalar
Proceedings of the Twelfth Language Resources and Evaluation Conference

In this paper we present a relation extraction system that given a text extracts pedagogically motivated relation types, as a previous step to obtaining a semantic representation of the text which will make possible to automatically generate questions for reading comprehension. The system maps pedagogically motivated relations with relations from ConceptNet and deploys Distant Supervision for relation extraction. We run a study on a subset of those relationships in order to analyse the viability of our approach. For that, we build a domain-specific relation extraction system and explore two relation extraction models: a state-of-the-art model based on transfer learning and a discrete feature based machine learning model. Experiments show that the neural model obtains better results in terms of F-score and we yield promising results on the subset of relations suitable for pedagogical purposes. We thus consider that distant supervision for relation extraction is a valid approach in our target domain, i.e. biology.

2016

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SemEval-2016 Task 2: Interpretable Semantic Textual Similarity
Eneko Agirre | Aitor Gonzalez-Agirre | Iñigo Lopez-Gazpio | Montse Maritxalar | German Rigau | Larraitz Uria
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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iUBC at SemEval-2016 Task 2: RNNs and LSTMs for interpretable STS
Iñigo Lopez-Gazpio | Eneko Agirre | Montse Maritxalar
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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UBC: Cubes for English Semantic Textual Similarity and Supervised Approaches for Interpretable STS
Eneko Agirre | Aitor Gonzalez-Agirre | Iñigo Lopez-Gazpio | Montse Maritxalar | German Rigau | Larraitz Uria
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability
Eneko Agirre | Carmen Banea | Claire Cardie | Daniel Cer | Mona Diab | Aitor Gonzalez-Agirre | Weiwei Guo | Iñigo Lopez-Gazpio | Montse Maritxalar | Rada Mihalcea | German Rigau | Larraitz Uria | Janyce Wiebe
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

2013

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EHU-ALM: Similarity-Feature Based Approach for Student Response Analysis
Itziar Aldabe | Montse Maritxalar | Oier Lopez de Lacalle
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)

2011

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Learning word-level dialectal variation as phonological replacement rules using a limited parallel corpus
Mans Hulden | Iñaki Alegria | Izaskun Etxeberria | Montse Maritxalar
Proceedings of the First Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties

2006

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Using Machine Learning Techniques to Build a Comma Checker for Basque
Iñaki Alegria | Bertol Arrieta | Arantza Diaz de Ilarraza | Eli Izagirre | Montse Maritxalar
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

1997

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From Psycholinguistic Modelling of Interlanguage in Second Language Acquisition to a Computational Model
Montse Maritxalar | Arantza Diaz de Ilarraza | Maite Oronoz
CoNLL97: Computational Natural Language Learning

1993

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A Morphological Analysis Based Method for Spelling Correction
I. Aduriz | E. Agirre | I. Alegria | X. Arregi | J.M Arriola | X. Artola | A. Diaz de Ilarraza | N. Ezeiza | M. Maritxalar | K. Sarasola | M. Urkia
Sixth Conference of the European Chapter of the Association for Computational Linguistics

1992

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XUXEN: A Spelling Checker/Corrector for Basque Based on Two-Level Morphology
E. Agirre | I Alegria | X Arregi | X Artola | A Diaz de Ilarraza | M Maritxalar | K Sarasola | M Urkia
Third Conference on Applied Natural Language Processing