Datasets:
Tasks:
Other
Sub-tasks:
coreference-resolution
Languages:
Hungarian
Tags:
structure-prediction
License:
ligetinagy
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README.md
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### Dataset Summary
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This is the dataset card for the Hungarian translation of the Winograd schemas. 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](hulu.nlp.nytud.hu). The corpus was created by translating and manually curating the original English Winograd
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### Languages
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### Data Instances
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For each instance, there is
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An example:
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"CorrectAnswer": "1"
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}
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```
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### Data Fields
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- id: unique id of the instances;
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- Answer2: the second possible reference;
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- CorrectAnswer: the number of the correct answer (1 or 2).
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### Data Splits
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#### Initial Data Collection and Normalization
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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.
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## Additional Information
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### Dataset Summary
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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](hulu.nlp.nytud.hu). 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).
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### Languages
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### Data Instances
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For each instance, there is a schema, an id, two sentences and a label.
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An example:
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```
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{"schema": "1",
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"id": "0",
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"sentence1": "A városi tanácstagok nem adtak engedélyt a tüntetőknek, mert kerülték az erőszakot.",
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"sentence2": "A városi tanácstagok kerülték az erőszakot.",
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"Label": "1"
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}
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```
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### Data Fields
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- schema: the number of the original schema this sentence pair was derived from;
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- id: unique id of the instances;
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- sentence1: the original sentence of the schema with one of the two alternate words;
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- sentence2: a manually formed question;
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- Label: "1" if sentence2 is entailed by sentence1, and "0" otherwise.
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### Data Splits
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#### Initial Data Collection and Normalization
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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.
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## Additional Information
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