Lilja Øvrelid

Exploiting survey and online patient experience comments in general practice: validating a fine-tuned language model for automatic sentiment analysis

Rebecka Maria Norman, Lilja Charlotte Storset, Petter Mæhlum, Hilde Hestad Iversen et autres

BACKGROUND: Automated sentiment analysis can be used to analyse free-text patient experience comments, but in health services research, it requires technical performance and methodological validity. Traditional models lack contextual understanding, whereas masked language models (MLMs) enable nuanced sentiment classification. This study is …

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A comprehensive survey of semantic role labeling in the era of pretrained language models

Huiyao Chen, Meishan Zhang, Jing Li, Lilja Øvrelid et autres

Entity-Level Sentiment Analysis with Sentence Relevance Detection

Egil Rønningstad, Roman Klinger, Lilja Øvrelid, Erik Velldal

Context Is (Almost) Everything: Llama-3 on Structured Output and AMR Parsing

Maja Buljan, Stephan Oepen, Lilja Øvrelid

MUC-4 Revisited: Document-level Event Analysis beyond Span-based Arguments

Helene Bøsei Olsen, Erik Velldal, Lilja Øvrelid

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Doğukan Arslan, Rodrigo Wilkens, Wei He et autres

Potentially idiomatic expressions (PIEs) carry meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challenge for assessing the linguistic (and to some extent cultural) capabilities of NLP systems. In this paper, we present …

Neural text sanitization with privacy risk indicators: an empirical analysis

Anthi Papadopoulou, Pierre Lison, Mark Anderson, Lilja Øvrelid et autres

Abstract Text sanitization is the task of redacting a document to mask all occurrences of (direct or indirect) personal identifiers, with the goal of concealing the identity of the individual(s) referred in it. In this paper, we consider a two-step approach to …

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Measuring Idiomaticity in Text Embedding Models with 𝜀-compositionality

Association for Computational Linguistics 2026, Lilja Øvrelid, Étienne Simon, Erik Velldal et autres

The principle of compositionality, which concerns the construction of meaning from constituent parts, is a longstanding topic in various disciplines, most commonly associated with formal semantics. In NLP, recent studies have focused on the compositional properties of text embedding models, particularly regarding …

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Coreference in Universal Dependencies 1.4 (CorefUD 1.4)

Michal Novák, Martin Popel, Daniel Zeman, Zdeněk Žabokrtský et autres

CorefUD is a collection of previously existing coreference-annotated datasets that have been converted to a unified annotation scheme. In its current version (1.4), CorefUD comprises 33 datasets covering 19 languages. The datasets are enriched with automatically assigned morphological and syntactic annotations, fully …

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He et autres

Potentially idiomatic expressions (PIEs) construe meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challenge for assessing the linguistic (and to some extent cultural) capabilities of NLP systems. In this paper, we present …

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He et autres

Potentially idiomatic expressions (PIEs) construe meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challenge for assessing the linguistic (and to some extent cultural) capabilities of NLP systems. In this paper, we present …

Measuring Idiomaticity in Text Embedding Models with epsilon-compositionality

Sondre Wold, Étienne Simon, Erik Velldal, Lilja Øvrelid

The principle of compositionality, which concerns the construction of meaning from constituent parts, is a longstanding topic in various disciplines, most commonly associated with formal semantics.In NLP, recent studies have focused on the compositional properties of text embedding models, particularly regarding their …

no (code pays fourni par la source)