Humanitate Digitalak eta Hezkuntza

In this article, we explain the first steps to-wards a grammar-helping tool for Basquefrom a ruled-based approach. Specifically,we show the first steps carried out for help-ing with verb agreement, some of the dif-ficulties encountered, which linguistic is-sues arise when new rules are designed,and future perspectives

Hizkuntzen ikas-irakaskuntzan hizkuntza-teknologiak egin dezakeen ekarpena azaltzea da artikulu honen helburua. Horretarako, hizkuntzalaritza konputazionala zer den eta eskolan zelan erabil daitekeen landuko da, alde batetik. Beste alde batetik, testuinguruari eta nazioarteko esperientziei gainbegirada orokorra emateaz gain, euskararen esparruan garatu diren baliabideei eta egiten ari diren ikerlanei ere erreparatuko zaie, etorkizuneko bideak eta erronkak alde batera utzi gabe.

Teknologiaren garapenak ez du etenik. Badirudi hainbat motako datuen bilketa (eta hein batean jakintza) negozio bihurtu dela eta enpresa handien eta pribatuen esku nabarmen geratzen ari dela. Datuen bilketa eta garapen mota horrek gure identitate digitala (eta bestelakoa) arriskuan jar dezake eta oro har arrakala digitala areagotu egin du, eremu publikoaren edo jendartearen esku dauden aukerak eta baliabideak murrizten direlako.

To detect how and when readers are experiencing engagement with a literary work, we bring together empirical literary studies and
language technology via focusing on the affective state of absorption. The goal of our resource development is to enable the detection
of different levels of reading absorption in millions of user-generated reviews hosted on social reading platforms. We present a corpus
of social book reviews in English that we annotated with reading absorption categories. Based on these data, we performed supervised,

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.

In this paper we present a relation extraction system that given a text extracts pedagogically motivated relation types, as a previousstep 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 Supervisionfor relation extraction. We run a study on a subset of those relationships in order to analyse the viability of our approach.