RT Journal Article
T1 Corpus annotation of functional discourse units for aspect‑based sentiment analysis
A1 Moreno-Ortiz, Antonio Jesús
A1 García Gámez, María
K1 Lingüística aplicada
K1 Corpus lingüístico - Proceso de datos
AB Aspect-based sentiment analysis (ABSA) aims to identify the sentiment associatedwith specifc aspects or entities in a text. In order to facilitate the development andevaluation of ABSA systems, it is crucial to have annotated datasets that containinformation about the aspects, entities, and the sentiments expressed towards them.However, the amount of information in existing datasets (for example those used inthe SemEval shared tasks) is very limited. We innovate on existing corpora by introducing a multi-layered annotation schema that includes not only entities and aspects,but also lexical items and, crucially, functional discourse units (FDUs). These FDUsare text segments (typically sentences or clauses) that play a specifc role or functionwithin the overall text, such as “description”, “evaluation”, or “advice”, a type ofinformation which we believe can be of great help in ABSA. Our corpus focuses onuser reviews of tourist attractions (specifcally monuments) in the region of Andalusia (Spain), but the same schema can be used to annotate reviews of other domainssimply by adapting the aspects layer, which is domain-dependent. The annotationschema is described, and the validation process is carried out on a sample of 400reviews from this domain. Results show a substantial level of agreement among theannotators, indicating that the schema is reliable and consistent. We go on to illustrate and discuss some difcult cases where annotation showed discrepancy amongannotators. The annotation of FDUs in the corpus is a signifcant advancement foraspect-based sentiment analysis.
PB Springer
YR 2025
FD 2025-07-08
LK https://hdl.handle.net/10630/39809
UL https://hdl.handle.net/10630/39809
LA eng
NO Moreno-Ortiz, A., García-Gámez, M. Corpus Annotation of Functional Discourse Units for Aspect-Based Sentiment Analysis. Corpus Pragmatics (2025). https://doi.org/10.1007/s41701-025-00199-0
NO Funding for open access charge: Universidad de Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026