| dc.contributor.author | Meden, Katja |
| dc.contributor.author | Logar, Tamara |
| dc.date.accessioned | 2026-07-09T10:01:11Z |
| dc.date.available | 2026-07-09T10:01:11Z |
| dc.date.issued | 2026-06-25 |
| dc.identifier.uri | http://hdl.handle.net/11356/2256 |
| dc.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. |
| dc.language.iso | slv |
| dc.publisher | Jožef Stefan Institute |
| dc.rights | Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) |
| dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ |
| dc.rights.label | PUB |
| dc.source.uri | https://github.com/katjameden/ParlaMint_Sentiment |
| dc.subject | sentiment classification |
| dc.subject | sentiment analysis |
| dc.subject | parliamentary debates |
| dc.subject | Slovenian Parliament |
| dc.title | Speech-level sentiment dataset of Slovenian parliamentary debates ParlaSent-SI 1.0 |
| dc.type | corpus |
| metashare.ResourceInfo#ContentInfo.mediaType | text |
| has.files | yes |
| branding | CLARIN.SI data & tools |
| contact.person | Katja Meden katja.meden@ijs.si Jožef Stefan Institute |
| sponsor | Jožef Stefan Institute CLARIN CLARIN.SI nationalFunds |
| sponsor | CLARIN ERIC - ParlaMint: Towards Comparable Parliamentary Corpora Other |
| sponsor | ARRS (Slovenian Research Agency) P2-103 Knowledge Technologies nationalFunds |
| size.info | 1000 utterances |
| size.info | 4 files |
| files.count | 1 |
| files.size | 1157134 |
Datoteke v tem vnosu
To je vnos
Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Publicly Available
z licenco:Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
- Ime
- ParlaSent-SI_1.0.zip
- Velikost
- 1.1 MB
- Format
- application/zip
- Opis
- Dataset in TSV and JSON with annotation guidelines and README
- MD5
- a1ca72b4c6e49109694037a182269743
- ParlaSent-SI_1.0
- README.md3 kB
- Speech-Level_Sentiment_Annotation_dataset.json1 MB
- Speech-Level_Sentiment_Annotation_dataset.tsv1 MB
- Speech-Level Sentiment annotation guidelines.pdf104 kB