Annotated Corpus of Czech Case Law for Reference Recognition Tasks (2019-06-25)
Please use the following text to cite this item or export to a predefined format:
Harašta, Jakub; et al., 2018,
Annotated Corpus of Czech Case Law for Reference Recognition Tasks (2019-06-25), LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL),
http://hdl.handle.net/11234/1-3008.
Authors
Harašta, Jakub ; et al.
Item identifier
Project URL
Date issued
2018
Size
350 articles
Language(s)
Description
Annotated corpus of 350 decision of Czech top-tier courts (Supreme Court, Supreme Administrative Court, Constitutional Court).
Every decision is annotated by two trained annotators and then manually adjudicated by one trained curator to solve possible disagreements between annotators. Adjudication was conducted non-destructively, therefore corpus (raw) contains all original annotations.
Corpus was developed as training and testing material for reference recognition tasks. Dataset contains references to other court decisions and literature. All references consist of basic units (identifier of court decision, identification of court issuing referred decision, author of book or article, title of book or article, point of interest in referred document etc.), values (polarity, depth of discussion etc.).
Publisher
Acknowledgement
Grantová agentura ČR
Project code:GA17-20645S
Project name:Exaktní hodnocení aplikační relevance judikatury
Subject(s)
Collections
Version History
This item isPublicly Available
and licensed under:
Files in this item
- Name
- ReadMe.pdf
- Size
- 1023.54 KB
- Format
- application/pdf
- Description
- ReadMe
- MD5
- dbed093e0225037c5475a8485a35e79d

The file preview has not been generated yet. Please try again later or contact the system administrator lindat-help@ufal.mff.cuni.cz
- Name
- corpus-gold.json
- Size
- 17.33 MB
- Format
- application/octet-stream
- Description
- Corpus (gold)
- MD5
- 8de4d70afb84fb380c87015514de3db9

The file preview has not been generated yet. Please try again later or contact the system administrator lindat-help@ufal.mff.cuni.cz
- Name
- corpus.json
- Size
- 47.56 MB
- Format
- application/octet-stream
- Description
- Corpus (raw)
- MD5
- af52cefc23807404d9a6c617af47a477

The file preview has not been generated yet. Please try again later or contact the system administrator lindat-help@ufal.mff.cuni.cz

