VytautoDidziojoUniversitetas/LT_Summarisation_Corpus

Lithuanian Summarisation Corpus

Description

Lithuanian texts paired with human-written abstractive and extractive summaries, spanning four subject domains — information technology, law, medicine, and media. The corpus is designed for training and evaluating summarisation systems on Lithuanian-language content, covering both technical and general registers.

Dataset summary

• Types of Dataset: CSV, JSON, XML
• Number of CSV files: 8 (4 training, 4 testing)
• Number of JSON files: 8 (4 training, 4 testing)
• Number of csv files: 1 (1 training, 1 testing)
• Total rows (texts): 2340 (2251 training, 100 testing)
• Total file size: 21 MB (20.3 MB training, 0.7 MB testing)

Main columns

• text: string
• summary_abstract: string
• summary_extract: string
• type: string

Data composition

All abstract corpora texts are in Lithuanian and are human-written. The corpus is collected from four domains (Type): IT (it), law (teisė), medicine (medicina), and news (žiniasklaida).

Type	Description	Sources
it	Information Technology articles	IT blogs (e.g., technologijos.lt); student bachelor's and master's theses (e.g., VDU CRIS); VU IT research journals (e.g., zurnalai.vu.lt).
teisė	Law documents	Lithuanian Courts Information System (LITEKO); Register of Legal Acts of the Republic of Lithuania; Supreme Court of Lithuania case law; legal publications (e.g., teise.pro); research articles (e.g., elaba.lt).
medicina	Medicine texts	Anonymized data prepared by the State Data Agency: pharmacy documents, doctors' diagnoses. Anonymized data prepared by the State Data Agency: pharmacy documents, doctors' diagnoses.
žiniasklaida	News articles	News articles from lrt.lt.

Distribution of text types

Text type	Text Word count	Abstractive Word count	Extractive Word count	Text count
it	344,710	65,403	89,131	689
teisė	668,276	155,893	224,446	533
medicina	371,611	64,980	89,570	550
žiniasklaida	354,012	66,315	91,714	568
Total	1,738,609	352,591	494,861	2340

Licensing

This dataset is distributed under the NewGenLTU OpenRAIL-D licence.

This licence was specifically created by a team of researchers at Vytautas Magnus University for the publication of datasets produced in the course of research and development projects funded by the New Generation Lithuania plan. The licence aims to support open and responsible downstream use while ensuring compliance with applicable requirements related to copyright, personal data protection, and the EU AI Act.

Please see the accompanying LICENSE.txt file in this repository for the full licence text.

Intended use

This dataset may be used for a range of Lithuanian-language NLP and AI tasks, including:

• text generation,
• summarisation,
• language modelling,
• grammar and style correction,
• semantic search,
• text analysis,
• virtual assistants,
• other language technology applications.

Restrictions

Under the NewGenLTU OpenRAIL-D licence, users must not use the dataset for:

• discrimination,
• the development of weapons or military applications,
• automated decision-making affecting people,
• disinformation,
• privacy infringement,
• medical or health advice,
• creation of malware,
• harassment,
• dishonest research,
• collection, extraction, or reconstruction of personal data.

Please refer to the accompanying LICENSE.txt file for the full and authoritative wording.

Limitations and bias

The developers made substantial efforts to clean the dataset and reduce noise, OCR errors, and duplicates. However, users should be aware of the following limitations:

• the corpus is strongly dominated by news portal texts (52%) and documents (38%), which may bias downstream models toward these registers and domains.

Citation

Please cite the dataset as:

Vytautas Magnus University and Vilnius University. 2026. Abstract Corpora for Artificial Intelligence. Hugging Face. https://huggingface.co/datasets/VytautoDidziojoUniversitetas/LT_Summarisation_Corpus

BibTeX:

@dataset{lt_acai_2026,
  author    = {{Vytautas Magnus University} and {Vilnius University}},
  title     = {Abstract Corpora for Artificial Intelligence},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/VytautoDidziojoUniversitetas/LT_Summarisation_Corpus},
  note      = {Developed under the New Generation Lithuania plan, project 02-101-K-0001.}
}

Acknowledgement

Funded by the European Union — NextGenerationEU. Naujos kartos Lietuva.

This project is funded by the Recovery and Resilience Facility under the Lithuanian "Naujos kartos Lietuva" plan and by the State Budget of the Republic of Lithuania.

Project: Santraukų tekstynai dirbtiniam intelektui — Project No. 02-101-K-0001.