README.md

metadata

YAML tags: null
annotations_creators:
  - found
language_creators:
  - found
  - expert-generated
languages:
  - hu
licenses:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
pretty_name: HuWNLI
size_categories:
  - unknown
source_datasets:
  - extended|other
task_categories:
  - structure-prediction
task_ids:
  - coreference-resolution

Dataset Card for HuWNLI

Table of Contents

• Table of Contents

• Dataset Description

  • Dataset Summary

  • Supported Tasks and Leaderboards

  • Languages

• Dataset Structure

  • Data Instances

  • Data Fields

  • Data Splits

• Dataset Creation

  • Curation Rationale

  • Source Data

  • Annotations

  • Personal and Sensitive Information

• Considerations for Using the Data

  • Social Impact of Dataset

  • Discussion of Biases

  • Other Known Limitations

• Additional Information

  • Dataset Curators

  • Licensing Information

  • Citation Information

  • Contributions

Dataset Description

• Homepage:
• Repository: HuWNLI dataset
• Paper:
• Leaderboard:
• Point of Contact: lnnoemi

Dataset Summary

This is the dataset card for the Hungarian translation of the Winograd schemas formatted as an inference task. A Winograd schema is a pair of sentences that differ in only one or two words and that contain an ambiguity that is resolved in opposite ways in the two sentences and requires the use of world knowledge and reasoning for its resolution (Levesque et al. 2012). This dataset is also part of the Hungarian Language Understanding Evaluation Benchmark Kit HuLU. The corpus was created by translating and manually curating the original English Winograd schemata. The NLI format was created by replacing the ambiguous pronoun with each possible referent (the method is described in GLUE's paper, Wang et al. 2019).

Languages

The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU.

Dataset Structure

Data Instances

For each instance, there is a schema, an id, two sentences and a label.

An example:

{"schema": "1",
 "id": "0",
 "sentence1": "A városi tanácstagok nem adtak engedélyt a tüntetőknek, mert kerülték az erőszakot.",
 "sentence2": "A városi tanácstagok kerülték az erőszakot.",
 "Label": "1"
}

Data Fields

• schema: the number of the original schema this sentence pair was derived from;

• id: unique id of the instances;

• sentence1: the original sentence of the schema with one of the two alternate words;

• sentence2: a manually formed question;

• Label: "1" if sentence2 is entailed by sentence1, and "0" otherwise.

Data Splits

The data is distributed without any predefined splits.

Dataset Creation

Source Data

Initial Data Collection and Normalization

The data is a translation of the English Winograd schemas. Each schema was translated by a human translator. Each translation was manually checked and further refined by another annotator. Each schema was manually curated by a linguistic expert. The schemata were transformed into nli format by a linguistic expert.

Additional Information

Licensing Information

HuWSC is released under the BCreative Commons Attribution-ShareAlike 4.0 International License.

Citation Information

If you use this resource or any part of its documentation, please refer to:

Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. In: Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika (eds), XVIII. Magyar Számítógépes Nyelvészeti Konferencia. JATEPress, Szeged. 431–446.

@inproceedings{ligetinagy2022hulu,
  title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából},
  author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.},
  booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
  year={2022},
  editors = {Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika},
  address = {Szeged},
  publisher = {JATEPress},
  pages = {431–446}
}

and to:

Levesque, Hector, Davis, Ernest, Morgenstern, Leora (2012) he winograd schema challenge. In: Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning.

@inproceedings{levesque2012winograd,
  title={The Winograd Schema Challenge},
  author={Levesque, Hector and Davis, Ernest and Morgenstern, Leora},
  booktitle={Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning},
  year={2012},
  organization={Citeseer}
}

Contributions

Thanks to lnnoemi for adding this dataset.