Begoña Altuna


pdf bib
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
Iker García-Ferrero | Begoña Altuna | Javier Alvez | Itziar Gonzalez-Dios | German Rigau
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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.


pdf bib
Proceedings of the Workshop Towards Digital Language Equality within the 13th Language Resources and Evaluation Conference
Itziar Aldabe | Begoña Altuna | Aritz Farwell | German Rigau
Proceedings of the Workshop Towards Digital Language Equality within the 13th Language Resources and Evaluation Conference


pdf bib
The Scope and Focus of Negation: A Complete Annotation Framework for Italian
Begoña Altuna | Anne-Lyse Minard | Manuela Speranza
Proceedings of the Workshop Computational Semantics Beyond Events and Roles

In this paper we present a complete framework for the annotation of negation in Italian, which accounts for both negation scope and negation focus, and also for language-specific phenomena such as negative concord. In our view, the annotation of negation complements more comprehensive Natural Language Processing tasks, such as temporal information processing and sentiment analysis. We applied the proposed framework and the guidelines built on top of it to the annotation of written texts, namely news articles and tweets, thus producing annotated data for a total of over 36,000 tokens.


pdf bib
MEANTIME, the NewsReader Multilingual Event and Time Corpus
Anne-Lyse Minard | Manuela Speranza | Ruben Urizar | Begoña Altuna | Marieke van Erp | Anneleen Schoen | Chantal van Son
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this paper, we present the NewsReader MEANTIME corpus, a semantically annotated corpus of Wikinews articles. The corpus consists of 480 news articles, i.e. 120 English news articles and their translations in Spanish, Italian, and Dutch. MEANTIME contains annotations at different levels. The document-level annotation includes markables (e.g. entity mentions, event mentions, time expressions, and numerical expressions), relations between markables (modeling, for example, temporal information and semantic role labeling), and entity and event intra-document coreference. The corpus-level annotation includes entity and event cross-document coreference. Semantic annotation on the English section was performed manually; for the annotation in Italian, Spanish, and (partially) Dutch, a procedure was devised to automatically project the annotations on the English texts onto the translated texts, based on the manual alignment of the annotated elements; this enabled us not only to speed up the annotation process but also provided cross-lingual coreference. The English section of the corpus was extended with timeline annotations for the SemEval 2015 TimeLine shared task. The “First CLIN Dutch Shared Task” at CLIN26 was based on the Dutch section, while the EVALITA 2016 FactA (Event Factuality Annotation) shared task, based on the Italian section, is currently being organized.