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26 results on '"Altuna, Begoña"'

1. A Hard Nut to Crack: Idiom Detection with Conversational Large Language Models

Author

Fornaciari, Francesca De Luca, Altuna, Begoña, Gonzalez-Dios, Itziar, and Melero, Maite

Subjects
Computer Science - Computation and Language
Abstract

In this work, we explore idiomatic language processing with Large Language Models (LLMs). We introduce the Idiomatic language Test Suite IdioTS, a new dataset of difficult examples specifically designed by language experts to assess the capabilities of LLMs to process figurative language at sentence level. We propose a comprehensive evaluation methodology based on an idiom detection task, where LLMs are prompted with detecting an idiomatic expression in a given English sentence. We present a thorough automatic and manual evaluation of the results and an extensive error analysis.

Published
2024

2. NoticIA: A Clickbait Article Summarization Dataset in Spanish

Author

García-Ferrero, Iker and Altuna, Begoña

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

We present NoticIA, a dataset consisting of 850 Spanish news articles featuring prominent clickbait headlines, each paired with high-quality, single-sentence generative summarizations written by humans. This task demands advanced text understanding and summarization abilities, challenging the models' capacity to infer and connect diverse pieces of information to meet the user's informational needs generated by the clickbait headline. We evaluate the Spanish text comprehension capabilities of a wide range of state-of-the-art large language models. Additionally, we use the dataset to train ClickbaitFighter, a task-specific model that achieves near-human performance in this task., Comment: Accepted in the journal Procesamiento del Lenguaje Natural

Published
2024

3. This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models

Author

García-Ferrero, Iker, Altuna, Begoña, Álvez, Javier, Gonzalez-Dios, Itziar, and Rigau, German

Subjects
Computer Science - Computation and Language
Abstract

Although large language models (LLMs) have apparently acquired a certain level of grammatical knowledge and the ability to make generalizations, they fail to interpret negation, a crucial step in Natural Language Processing. We try to clarify the reasons for the sub-optimal performance of LLMs understanding negation. We introduce a large semi-automatically generated dataset of circa 400,000 descriptive sentences about commonsense knowledge that can be true or false in which negation is present in about 2/3 of the corpus in different forms. We have used our dataset with the largest available open LLMs in a zero-shot approach to grasp their generalization and inference capability and we have also fine-tuned some of the models to assess whether the understanding of negation can be trained. Our findings show that, while LLMs are proficient at classifying affirmative sentences, they struggle with negative sentences and lack a deep understanding of negation, often relying on superficial cues. Although fine-tuning the models on negative sentences improves their performance, the lack of generalization in handling negation is persistent, highlighting the ongoing challenges of LLMs regarding negation understanding and generalization. The dataset and code are publicly available., Comment: Accepted in the The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)

Published
2023

4. European Clinical Case Corpus

Author

Magnini, Bernardo, Altuna, Begoña, Lavelli, Alberto, Minard, Anne-Lyse, Speranza, Manuela, Zanoli, Roberto, Sonntag, Daniel, Editor-in-Chief, and Rehm, Georg, editor

Published
2023
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5. European Clinical Case Corpus

Author

Magnini, Bernardo, primary, Altuna, Begoña, additional, Lavelli, Alberto, additional, Minard, Anne-Lyse, additional, Speranza, Manuela, additional, and Zanoli, Roberto, additional

Published
2022
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6. Adapting TimeML to Basque: Event Annotation

Author

Altuna, Begoña, Aranzabe, María Jesús, Díaz de Ilarraza, Arantza, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, and Gelbukh, Alexander, editor

Published
2018
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10. Overview of TESTLINK at IberLEF 2023: Linking Results to Clinical Laboratory Tests and Measurements.

Author

Altuna, Begoña, Agerri, Rodrigo, Salas-Espejo, Lidia, Javier Saiz, José, Lavelli, Alberto, Magnini, Bernardo, Speranza, Manuela, Zanoli, Roberto, and Karunakaran, Goutham

Subjects
DEEP learning, PATHOLOGICAL laboratories, DATA mining
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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12. The E3C Project: Collection and Annotation of a Multilingual Corpus of Clinical Cases

Author

Magnini, Bernardo, Altuna, Begoña, Lavelli, Alberto, Speranza, Manuela, and Zanoli, Roberto

Subjects
Twitter during Pandemic, Automatic Sarcasm Detection, Linguistic Ostracism in Social Networks, AriEmozione, COVID-19, Linguistics, LAN000000, Quantitative Linguistic Investigations, Fine-grained sentiment analysis, Online Hate Speech, Computational Linguistics, DistilBERT, Depression from Social Media, Distributional Semantics, Gender Bias, CBX, AEREST, E3C Project, Multilingual NLU, TrAVaSI
Abstract

We present the European Clinical Case Corpus (E3C) project, aimed at collecting and annotating a large corpus of clinical cases in five European languages (Italian, English, French, Spanish, and Basque). Project results include: (i) a freely available collection of multilingual clinical cases; and (ii) a two-level annotation scheme based on temporal relations (derived from THYME), whose purpose is to allow the construction of clinical timelines, and taxonomy relations based on medical taxonomies, to be used for semantic reasoning over clinical cases.

Published
2021

13. Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

Author

Altuna, Begoña, Alzetta, Chiara, Anselma, Luca, Antinori, Alessandro, Aprosio, Alessio Palmero, Ardito, Luca, Argese, Chiara, Bacco, Luca, Baisa, Vít, Balaraman, Vevake, Barrón-Cedeño, Alberto, Basile, Pierpaolo, Basile, Valerio, Basili, Roberto, Bassignana, Elisa, Benvenuti, Nicola, Bernardi, Raffaella, Bertino, Enrico, Biasion, Davide, Biffi, Marco, Bolioli, Andrea, Bonadiman, Daniele, Bonora, Paolo, Bosca, Alessio, Bosco, Cristina, Brambilla, Silvia, Brunato, Dominique, Bucur, Ana-Maria, Cafagna, Michele, Caligiore, Gaia, Cappa, Claudia, Caputo, Annalina, Carlino, Carola, Caselli, Tommaso, Cassotti, Pierluigi, Castagnoli, Sara, Casula, Camilla, Cecchini, Flavio M., Celli, Fabio, Cervone, Alessandra, Chiusaroli, Francesca, Chung, Yi-Ling, Cignarella, Alessandra Teresa, Cimino, Andrea, Colla, Davide, Coltrinari, Riccardo, Colucci, Ilaria, Corino, Elisa, Croce, Danilo, Dell’Orletta, Felice, Delsanto, Matteo, de Gemmis, Marco, De Mattei, Lorenzo, de Varda, Andrea Gregor, Dinu, Liviu P., di Buono, Maria Pia, Di Gangi, Mattia Antonino, Di Lascio, Mirko, Ducret, Martina, Fabris, Alessandro, Falco, Mariacristina, Favalli, Andrea, Favaro, Manuel, Feldman, Anna, Fernández, Raquel, Fernicola, Francesco, Ferro, Marcello, Franzini, Greta, Gabrieli, Giuliano, Gagliardi, Gloria, Gaido, Marco, Gandolfi, Greta, Garcea, Federico, Gatt, Albert, Gemmis, Marco de, Giannone, Cristina, Giulivi, Sara, Gregori, Lorenzo, Gualdoni, Eleonora, Guerini, Marco, Hoste, Veronique, Iavarone, Benedetta, Jezek, Elisabetta, Karakanta, Alina, Kopp, Stefan, Kruse, Lauren, Lavelli, Alberto, Lenci, Alessandro, Liello, Luca Di, Lim, Alfred, Lops, Pasquale, Louvan, Samuel, Magnini, Bernardo, Mambrini, Francesco, Mana, Dario, Manna, Raffaele, Marino, Gian Manuel, Martinez, Carlos, Marzi, Claudia, Masini, Francesca, Mattei, Andrea, Mazzei, Alessandro, Menini, Stefano, Mensa, Enrico, Merone, Mario, Miaschi, Alessio, Micheli, M. Silvia, Montemagni, Simonetta, Monti, Johanna, Moretti, Giovanni, Morisio, Maurizio, Moschitti, Alessandro, Muffo, Matteo, Musto, Cataldo, Nadalini, Andrea, Negri, Matteo, Nissim, Malvina, Nolano, Gennaro, Nuovo, Elisa Di, Oliveri, Isabeau, Onnis, Luca, Origlia, Antonio, Osenova, Petya, O’Brien, Beth A., Palmero Aprosio, Alessio, Papa, Sirio, Pascucci, Antonio, Passarotti, Marco, Patti, Viviana, Paulon, Luca, Pellegrini, Matteo, Pelosi, Serena, Peng, Jing, Pezzelle, Sandro, Pierucci, Maria Laura, Pirinen, Tommi A., Pirrelli, Vito, Polignano, Marco, Radicioni, Daniele P., Ravelli, Andrea Amelio, Rescigno, Argentina Anna, Riccardi, Giuseppe, Rizzo, Giuseppe, Roberti, Pierluigi, Roccabruna, Gabriel, Rodella, Anna, Romagnoli, Raniero, Romani, Emma, Ruggiero, Gaetana, Sanguinetti, Manuela, Sarti, Gabriele, Semeraro, Giovanni, Silvello, Gianmaria, Simeoni, Rossana, Simi, Maria, Simoniello, Vincenzo, Simov, Kiril, Speranza, Giulia, Speranza, Manuela, Spillo, Giuseppe, Sprugnoli, Rachele, Strapparava, Carlo, Sucameli, Irene, Suozzi, Alice, Susto, Gian Antonio, Tamburini, Fabio, Taxitari, Loukia, Tekiroğlu, Serra Sinem, Testoni, Alberto, Tonelli, Sara, Tripodi, Rocco, Trosterud, Trond, Turchi, Marco, Uva, Antonio, Vanmassenhove, Eva, Varvara, Rossella, Vassallo, Marco, Venturi, Giulia, Vigorelli, Pietro, Vitale, Pierluigi, Way, Andy, Wiechetek, Linda, Yavuz, Mehmet Can, Zampedri, Federica, Zaninello, Andrea, Zanoli, Roberto, Zarino, Wanda Punzi, Zhang, Shibingfeng, Dell'Orletta, Felice, Monti, Johanna, and Tamburini, Fabio

Subjects
Twitter during Pandemic, Automatic Sarcasm Detection, Linguistic Ostracism in Social Networks, AriEmozione, COVID-19, Linguistics, LAN000000, Quantitative Linguistic Investigations, Fine-grained sentiment analysis, Online Hate Speech, Computational Linguistics, DistilBERT, Depression from Social Media, Distributional Semantics, Gender Bias, CBX, AEREST, E3C Project, Multilingual NLU, TrAVaSI
Abstract

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges.

Published
2021

15. Creating vocabulary exercises through NLP

Author

Aguirrezabal Zabaleta, Manex, Altuna, Begoña, Gil-Vallejo, Lara, Goikoetxea, Josu, Gonzalez-Dios, Itziar, Aguirrezabal Zabaleta, Manex, Altuna, Begoña, Gil-Vallejo, Lara, Goikoetxea, Josu, and Gonzalez-Dios, Itziar

Abstract

The use of technologies in Humanities opens new research op-portunities as it allows the access to vast amounts of data such as textualcorpora. As, in the Digital Humanities domain, a considerable amount ofthe research is done on digitised corpora, Natural Language Processing toolscan be of much help in their exploitation for they help extracting linguisticinformation. We present a series of experiments in which we propose texttransformations to generate vocabulary learning exercises based on NaturalLanguage Processing. We describe the corpus, databases and tools we haveemployed in our approach and we offer an overview of a multilingual languageprocessing pipeline. Then we present the experiments and their output. Wefinally discuss the strengths and shortcomings of our approach

Published
2019

16. Análisis de estructuras temporales en euskera y creación de un corpus.

Author

Altuna, Begoña

Subjects
PROGRAMMING languages, BASQUE language, COMPUTER systems, DATA mining, CORPORA, DEAMINATION
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2020

17. Euskarazko denbora-egiturak etiketatzeko gidalerroak v2.0

Author

Altuna, Begoña, Aranzabe Urruzola, María Jesús, and Díaz de Ilarraza Sánchez, María Aranzazu

Subjects
TimeML etiketatze-lengoaia, denbora-adierazpenak, denbora-egiturak, gertaerak
Abstract

[EN]To interpret the temporal information on texts, a mark-up language that will code that information is needed, in order to make that information automatically reachable. The most used mark-up language is TimeML (Pustejovsky et al., 2003), which has also been choosen for Basque. In this guidelines we present the Basque version of ISO-TimeML (ISO-TimeML working group, 2008). After having analysed the tags, attributes and values created for English, we describe the most appropriate ones to represent Basque time structures’ information. [EU]Testuetan agertzen den denborazko informazioa interpretatu ahal izateko, informazio hori kodetuko duen markaketa-lengoaia behar da, gerora informazio hori automatikoki baliatu ahal izateko. TimeML (Pustejovsky et al., 2003) etiketatze-lengoaia da zabalduena eta euskararako ere erabili dena. Lan honetan ISO-TimeMLren (ISO-TimeML working group, 2008) euskararako moldaketa aurkezten da; ingeleserako sortutako etiketa, atributu eta horien balioak aztertu ostean, euskarazko denbora-egituren informazioa hobekien islatzen dituztenak deskribatzen dira, hain zuzen ere.

Published
2016

19. Euskarazko denbora-informazioaren tratamendu automatikoa TimeMLren eta HeidelTimeren bidez

Author

Altuna, Begoña, Aranzabe Urruzola, María Jesús, Díaz de Ilarraza Sánchez, Arantza, Altuna, Begoña, Aranzabe Urruzola, María Jesús, and Díaz de Ilarraza Sánchez, Arantza

Abstract

Hizkuntzaren prozesamenduan (HP), denbora-informazioa beharrezkoa da testuak ulertzeko, testuko gertaerak noiz jazotzen diren edo zenbat irauten duten adierazten baitu. Artikulu honetan, euskarazko denbora-informazioaren azterketa eta prozesamendua aurkezten dira. Lehenik, denbora-egituren deskribapena egin da. Bigarren, informazio egituratua emateko markaketa-lengoaia eta horren bidez etiketatutako corpusak azaldu dira. Ondoren, etiketatzeko tresna automatikoa ere deskribatzen da eta lehen etiketatze automatikoaren saiakera bat eta horren emaitzak ere ematen dira.; Temporal information is compulsory for textual comprehension, since it describes when the events in text happen or their duration. In this article temporal information and processing are presented. First the temporal constructions are described. Secondly, the mark-up language that structures the data and the annotated corpora following it are shown. Finally, we describe automatic tool for annotation and a first automatic annotation effort and its results are also described.

Published
2016

20. Euskarazko denbora-egiturak etiketatzeko gidalerroak v2.0

Author

Lenguajes y sistemas informáticos, Hizkuntza eta sistema informatikoak, Altuna, Begoña, Aranzabe Urruzola, María Jesús, Díaz de Ilarraza Sánchez, María Aranzazu, Lenguajes y sistemas informáticos, Hizkuntza eta sistema informatikoak, Altuna, Begoña, Aranzabe Urruzola, María Jesús, and Díaz de Ilarraza Sánchez, María Aranzazu

Abstract

[EN]To interpret the temporal information on texts, a mark-up language that will code that information is needed, in order to make that information automatically reachable. The most used mark-up language is TimeML (Pustejovsky et al., 2003), which has also been choosen for Basque. In this guidelines we present the Basque version of ISO-TimeML (ISO-TimeML working group, 2008). After having analysed the tags, attributes and values created for English, we describe the most appropriate ones to represent Basque time structures’ information., [EU]Testuetan agertzen den denborazko informazioa interpretatu ahal izateko, informazio hori kodetuko duen markaketa-lengoaia behar da, gerora informazio hori automatikoki baliatu ahal izateko. TimeML (Pustejovsky et al., 2003) etiketatze-lengoaia da zabalduena eta euskararako ere erabili dena. Lan honetan ISO-TimeMLren (ISO-TimeML working group, 2008) euskararako moldaketa aurkezten da; ingeleserako sortutako etiketa, atributu eta horien balioak aztertu ostean, euskarazko denbora-egituren informazioa hobekien islatzen dituztenak deskribatzen dira, hain zuzen ere.

Published
2016

21. Basque time structures. Analysis and annotating experiment

Author

Altuna, Begoña, Aranzabe, María Jesús, and Díaz de Ilarraza, Arantza

Subjects
lexical triggers, lcsh:Language and Literature, lcsh:Philology. Linguistics, lcsh:P1-1091, time expressions, lcsh:P, time function words, denborazko erlazio-hitzak, denbora-adierazpenak, abiarazle lexikoak, Time information, Denbora-informazioa
Abstract

Denbora-informazioa erauztea oso erabilgarria da hizkuntzaren prozesamenduan (HP), besteak beste, testuen sinplifikazioan, informazio-erauzketako eta itzulpen automatikoko sistemetan balia baitaiteke. Lan honetan, euskaraz informazio hori baliagarri bihurtzeko egin diren lehen urratsak azaltzen dira: batetik, euskaraz denbora adierazteko erabiltzen diren egiturak zein eratakoak diren aztertu da gramatiketan oinarrituta, eta bestetik, egitura horiek testuetan etiketatzeko lehen erabakiak hartu dira. Halaber, ekonomiari buruzko corpus bat osatuta egin den etiketatze-lanaren esperimentua azaltzen da.

Published
2014

23. Euskarazko denbora-egiturak etiketatzeko gidalerroak v1.0

Author

Lenguajes y sistemas informáticos, Hizkuntza eta sistema informatikoak, Altuna, Begoña, Aranzabe Urruzola, María Jesús, Díaz de Ilarraza Sánchez, María Aranzazu, Lenguajes y sistemas informáticos, Hizkuntza eta sistema informatikoak, Altuna, Begoña, Aranzabe Urruzola, María Jesús, and Díaz de Ilarraza Sánchez, María Aranzazu

Abstract

To interpret the temporal information on texts, a mark-up language that will code that information is needed, in order to make that information automatically reachable. The most used mark-up language is TimeML (Pustejovsky et al., 2003), which has also been choosen for Basque. In this guidelines we present the Basque version of ISO-TimeML (ISO-TimeML working group, 2008). After having analysed the tags, attributes and values created for English, we describe the most appropriate ones to represent Basque time structures’ information., Testuetan agertzen den denborazko informazioa interpretatu ahal izateko, informazio hori kodetuko duen markaketa-lengoaia behar da, gerora informazio hori automatikoki baliatu ahal izateko. TimeML (Pustejovsky et al., 2003) etiketatze-lengoaia da zabalduena eta euskararako ere erabili dena. Lan honetan ISO-TimeMLren (ISO-TimeML working group, 2008) euskararako moldaketa aurkezten da; ingeleserako sortutako etiketa, atributu eta horien balioak aztertu ostean, euskarazko denbora-egituren informazioa hobekien islatzen dituztenak deskribatzen dira, hain zuzen ere.

Published
2014

24. EusHeidelTime: Time Expression Extraction and Normalisation for Basque.

Author

Altuna, Begoña, Aranzabe, María Jesús, and de Ilarraza, Arantza Díaz

Subjects
DATA mining, CORPORA
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2017

25. NewsReader project.

Author

Agerri, Rodrigo, Agirre, Eneko, Aldabe, Itziar, Altuna, Begoña, Beloki, Zuhaitz, Laparra, Egoitz, De Lacalle, Maddalen López, Rigau, German, Soroa, Aitor, and Urizar, Ruben

Subjects
NEWSREADERS (Computer software), EXTRACTION (Linguistics), LANGUAGE & languages, BROADCAST journalism, INFORMATION resources
Abstract

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2014

26. National Language Technology Platform for Public Administration

Author

Tadić, Marko, Farkaš, Daša, Filko, Matea, Vasiļevskis, Artūrs, Vasiļjevs, Andrejs, Ziediņš, Jānis, Motika, Željka, Fishel, Mark, Loftsson, Hrafn, Guðnason, Jón, Borg, Claudia, Cortis, Keith, Attard, Judie, Spiteri, Donatienne, Aldabe, Itziar, Altuna, Begoña, Farwell, Aritz, and Rigau, German

Subjects
machine translation, CAT tools, parallel corpora, National Language Technology Platform
Abstract

This article presents the work in progress on the collaborative project of several European countries to develop National Language Technology Platform (NLTP). The project aims at combining the most advanced Language Technology tools and solutions in a new, state- of-the-art, Artificial Intelligence driven, National Language Technology Platform for five EU/EEA official and lower- resourced languages.

Published
2022

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