Speech-level sentiment dataset of Slovenian parliamentary debates ParlaSent-SI 1.0

  Authors

Meden, Katja and Logar, Tamara

  Item identifier

http://hdl.handle.net/11356/2256

 Project URL

https://github.com/katjameden/ParlaMint_Sentiment

 Date issued

2026-06-25

 Type

corpus, text

 Size

1000 utterances, 4 files

 Language(s)

Slovenian

 Description

The dataset comprises 1,000 manually annotated full utterances (i.e., speeches) from the parliamentary proceedings of Slovenia, extracted from the ParlaMint-SI 4.1 corpus (http://hdl.handle.net/11356/1912). The manual annotation campaign closely follows the setup used for the ParlaSent 1.0 multilingual sentiment dataset of parliamentary debates (http://hdl.handle.net/11356/1868), which provides sentiment annotations at sentence level. The ParlaSent-SI instances were randomly sampled and each speech was independently annotated by two trained annotators. The annotators underwent extensive training and also participated in the sentence-level sentiment annotation for the ParlaSent 1.0 dataset. The six-level annotation schema, originally based on the framework proposed by Batanović et al. (2020, DOI: https://doi.org/10.1371/journal.pone.0242050), was retained from the sentence-level annotation campaign and only minimally adapted in wording to suit full-utterance annotation: • Positive for utterances that are predominantly positive • Negative for utterances that are predominantly negative • M_Positive for utterances that convey an ambiguous sentiment or a mixture of sentiments, but lean more towards the positive sentiment • M_Negative for utterances that convey an ambiguous sentiment or a mixture of sentiments, but lean more towards the negative sentiment • P_Neutral for utterances that only contain non-sentiment-related statements, but still lean more towards the positive sentiment • N_Neutral for utterances that only contain non-sentiment-related statements, but still lean more towards the negative sentiment. The final annotation for each utterance was determined in a separate reconciliation session, where the annotators reviewed their disagreements and agreed on the final tag. The 3-class labels (Positive, Negative, Neutral) are also provided. The dataset includes both procedural (i.e., those spoken by the session chair) and non-procedural parliamentary utterances. Procedural utterances are indicated in the "chair" column. Inter-annotator agreement (Krippendorff’s α) is reported for the full dataset and the non-procedural subset: 6-class schema: 0.724 (full dataset), 0.570 (non-procedural subset) 3-class schema: 0.852 (full dataset), 0.744 (non-procedural subset) The datasets are provided in both TSV and JSON formats and contain the initial annotations, annotator comments, procedural/non-procedural flag, flag for hard cases and the reconciled final label for 6- and 3-class sentiment annotation.

 Publisher

Jožef Stefan Institute

 Acknowledgement

Jožef Stefan Institute CLARIN "CLARIN.SI"

CLARIN ERIC - "ParlaMint: Towards Comparable Parliamentary Corpora"

ARRS (Slovenian Research Agency) P2-103 "Knowledge Technologies"

 Subject(s)

sentiment classification sentiment analysis parliamentary debates Slovenian Parliament

 Collection(s)

CLARIN.SI data & tools

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