Search Results for author: Itziar Aldabe

Found 12 papers, 1 papers with code

Does Corpus Quality Really Matter for Low-Resource Languages?

no code implementations15 Mar 2022 Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri, Olatz Perez-de-Viñaspre, Aitor Soroa

The vast majority of non-English corpora are derived from automatically filtered versions of CommonCrawl.

Domain Adapted Distant Supervision for Pedagogically Motivated Relation Extraction

no code implementations LREC 2020 Oscar Sainz, Oier Lopez de Lacalle, Itziar Aldabe, Montse Maritxalar

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.

Reading Comprehension Relation Extraction +1

Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions

no code implementations LREC 2020 Andrea Horbach, Itziar Aldabe, Marie Bexte, Oier Lopez de Lacalle, Montse Maritxalar

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.

Reading Comprehension

Multilingual and Cross-lingual Timeline Extraction

no code implementations2 Feb 2017 Egoitz Laparra, Rodrigo Agerri, Itziar Aldabe, German Rigau

In this paper we present an approach to extract ordered timelines of events, their participants, locations and times from a set of multilingual and cross-lingual data sources.

A Multilingual Predicate Matrix

no code implementations LREC 2016 Maddalen Lopez de Lacalle, Egoitz Laparra, Itziar Aldabe, German Rigau

This paper presents the Predicate Matrix 1. 3, a lexical resource resulting from the integration of multiple sources of predicate information including FrameNet, VerbNet, PropBank and WordNet.

Supervised Hierarchical Classification for Student Answer Scoring

no code implementations13 Jul 2015 Itziar Aldabe, Oier Lopez de Lacalle, Iñigo Lopez-Gazpio, Montse Maritxalar

This paper describes a hierarchical system that predicts one label at a time for automated student response analysis.

Classification General Classification

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