
# Icelandic WinoGrande dataset

This is the Icelandic WinoGrande dataset described in the IceBERT paper https://aclanthology.org/2022.lrec-1.464.pdf .

## Translation and localization
The records were manually translated and localized (skipped if localization was not possible) from English.
For the examples which were singlets instead of sentence pairs we added a corresponding sentence.
The "translations per se" are not exact since accurately preserving the original semantics is unimportant.
E.g., for some words, it was too difficult or impossible to match all constraints (gender, number, and case must not give the answer away for free, and changing gender means using a different lexical item); for others, the word choice simply didn't work.

Due to the inflections each candidate word had to be selected with extreme precision so we could not find any use with machine translation, neither as a starting point nor as a reference.

## Citation
If you make use of this dataset pleace cite

```
@inproceedings{snaebjarnarson-etal-2022-warm,
    title = "A Warm Start and a Clean Crawled Corpus - A Recipe for Good Language Models",
    author = "Sn{\ae}bjarnarson, V{\'e}steinn  and
      S{\'\i}monarson, Haukur Barri  and
      Ragnarsson, P{\'e}tur Orri  and
      Ing{\'o}lfsd{\'o}ttir, Svanhv{\'\i}t Lilja  and
      J{\'o}nsson, Haukur  and
      Thorsteinsson, Vilhjalmur  and
      Einarsson, Hafsteinn",
    editor = "Calzolari, Nicoletta  and
      B{\'e}chet, Fr{\'e}d{\'e}ric  and
      Blache, Philippe  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.464",
    pages = "4356--4366",
    abstract = "We train several language models for Icelandic, including IceBERT, that achieve state-of-the-art performance in a variety of downstream tasks, including part-of-speech tagging, named entity recognition, grammatical error detection and constituency parsing. To train the models we introduce a new corpus of Icelandic text, the Icelandic Common Crawl Corpus (IC3), a collection of high quality texts found online by targeting the Icelandic top-level-domain .is. Several other public data sources are also collected for a total of 16GB of Icelandic text. To enhance the evaluation of model performance and to raise the bar in baselines for Icelandic, we manually translate and adapt the WinoGrande commonsense reasoning dataset. Through these efforts we demonstrate that a properly cleaned crawled corpus is sufficient to achieve state-of-the-art results in NLP applications for low to medium resource languages, by comparison with models trained on a curated corpus. We further show that initializing models using existing multilingual models can lead to state-of-the-art results for some downstream tasks.",
}
```
language:is license:cc-by-4.0 region:us
{"language": ["is"], "license": "cc-by-4.0"}
TAGS
#language-Icelandic #license-cc-by-4.0 #region-us 


# Icelandic WinoGrande dataset

This is the Icelandic WinoGrande dataset described in the IceBERT paper URL .

## Translation and localization
The records were manually translated and localized (skipped if localization was not possible) from English.
For the examples which were singlets instead of sentence pairs we added a corresponding sentence.
The "translations per se" are not exact since accurately preserving the original semantics is unimportant.
E.g., for some words, it was too difficult or impossible to match all constraints (gender, number, and case must not give the answer away for free, and changing gender means using a different lexical item); for others, the word choice simply didn't work.

Due to the inflections each candidate word had to be selected with extreme precision so we could not find any use with machine translation, neither as a starting point nor as a reference.

If you make use of this dataset pleace cite


# Icelandic WinoGrande dataset

This is the Icelandic WinoGrande dataset described in the IceBERT paper URL . ## Translation and localization
The records were manually translated and localized (skipped if localization was not possible) from English.
For the examples which were singlets instead of sentence pairs we added a corresponding sentence.
The "translations per se" are not exact since accurately preserving the original semantics is unimportant.
E.g., for some words, it was too difficult or impossible to match all constraints (gender, number, and case must not give the answer away for free, and changing gender means using a different lexical item); for others, the word choice simply didn't work.

Due to the inflections each candidate word had to be selected with extreme precision so we could not find any use with machine translation, neither as a starting point nor as a reference.

If you make use of this dataset pleace cite
TAGS
#language-Icelandic #license-cc-by-4.0 #region-us 
 # Icelandic WinoGrande dataset

This is the Icelandic WinoGrande dataset described in the IceBERT paper URL . ## Translation and localization
The records were manually translated and localized (skipped if localization was not possible) from English.
For the examples which were singlets instead of sentence pairs we added a corresponding sentence.
The "translations per se" are not exact since accurately preserving the original semantics is unimportant.
E.g., for some words, it was too difficult or impossible to match all constraints (gender, number, and case must not give the answer away for free, and changing gender means using a different lexical item); for others, the word choice simply didn't work.

Due to the inflections each candidate word had to be selected with extreme precision so we could not find any use with machine translation, neither as a starting point nor as a reference.

If you make use of this dataset pleace cite