Data · dataset · 2023
Text2Story Lusa Annotated Corpus
Listed in INESC TEC Research Data Repository
Description
The Text2Story Lusa Annotated Corpus dataset contains multi-layered manual annotations for 117 articles from the Text2Story Lusa dataset. This resource includes both the text files (.txt) and the annotations in BRAT format (.ann). This dataset was initially developed in the context of the project "Text2Story: Extracting journalistic narratives from text and representing them in a narrative modeling language" / NORTE-01-0145-FEDER-03185. **To request access to this dataset please fill out this form (Text2Story Lusa Annotated Corpus - Request Form) and send it to: joao.a.castro@inesctec.pt** The **Text2Story Annotation Manual** is also available with the resource.
If you use this resource, please use the following citations (paper and dataset): Nunes, S., Jorge, A., Amorim, A., Sousa, H., Leal, A., Silvano, P., Cantante, I.& Campos, R. (2024). Text2Story Lusa: A Dataset for Narrative Analysis in European Portuguese News Articles. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024).
Read the rest (1 more)
Silvano, P., Jorge, A., Leal, A., Amorim, E., Sousa, H., Cantante, I., Campos, R., & Nunes, S. (2023). Text2Story Lusa Annotated Corpus [Data set]. INESC TEC. doi.org/10.25747/ESFS-1P16
Links
Get the data
- Text2Story Lusa Annotated - Request Form repositorio.inesctec.pt/bitstreams/5f67baa0-a8d2-4609-80bb-d191f245b022/download ↗
download · from rdm inesctec pt
Where it is published
- INESC TEC Research Data Repository dataset page rdm.inesctec.pt/dataset/cs-2023-018 ↗
landing page · from rdm inesctec pt
Catalogue records · 1
- CKAN API rdm.inesctec.pt/api/3/action/package_show?id=dc2c6da7-16c9-4c05-a2c7-27dae2f9c… ↗
metadata API · from rdm inesctec pt
Topics
- From keywords
- Computer Science & AI · Engineering
- Inferred from text
- Text 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| INESC TEC Research Data Repository | dc2c6da7-16c9-4c05-a2c7-27dae2f9c936 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:computer-science-ai | mapping · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| concepts[field].local:field:engineering | mapping · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · rdm inesctec pt | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| description | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | /notes |
| license_text | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| publication_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| title | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | /title |
| updated_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 |