README.md

---
language:
- gl
task_categories:
- question-answering
- multiple-choice
- text-generation
pretty_name: xstorycloze_gl
dataset_info:
  config_name: gl
  features:
  - name: InputStoryid
    dtype: string
  - name: InputSentence1
    dtype: string
  - name: InputSentence2
    dtype: string
  - name: InputSentence3
    dtype: string
  - name: InputSentence4
    dtype: string
  - name: RandomFifthSentenceQuiz1
    dtype: string
  - name: RandomFifthSentenceQuiz2
    dtype: string
  - name: AnswerRightEnding
    dtype: int32
  splits:
  - name: train
    num_examples: 360
  - name: test
    num_examples: 1511
configs:
- config_name: gl
  data_files:
  - split: train
    path: XStoryCloze_train_gl.tsv
  - split: test
    path: XStoryCloze_test_gl.tsv
  default: true
license: cc-by-4.0
size_categories:
- 1K<n<10K
---

# Dataset Card for xstorycloze_gl

<!-- Provide a quick summary of the dataset. -->

xstorycloze_gl is a question answering dataset in Galician, translated from the [English StoryCloze dataset](https://cs.rochester.edu/nlp/rocstories/).

## Dataset Details

### Dataset Description

xstorycloze_gl is based on multiple-choice narrative completions. The dataset consists of 360 instances in the train split and 1511 instances in the test split. Each instance contains a story stem, divided in 4 sentences, 2 possible completions, and the number indicating the correct answer.

- **Curated by:** [Proxecto Nós](https://doagalego.nos.gal/)
- **Language(s) (NLP):** Galician
- **License:** [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/)

### Dataset Sources

- **Repository:** [Proxecto NÓS at HuggingFace](https://huggingface.co/proxectonos)


## Uses

xstorycloze_gl is intended to evaluate reading comprehension of language models. Some suitable use cases for the dataset are:

- Common sense reasoning: xstorycloze_ca contains stories that require basic background knowledge, such as the cost of things or the consequences of social interactions.
- Casuality understanding: The stories in xstorycloze_ca are full of temporal and causal relationships between events, which requires a coherent way of understanding causality in narratives.
- Multiple choice test: For each story, xstorycloze_ca has 2 different completions which require reasoning between different options.
- Reading comprehension: Problems and answers in xstorycloze_ca are formulated in natural language.


## Dataset Structure

The dataset is provided in CSV format where each row corresponds to a four-sentence story and contains an instance identifier, the story divided in four fields for each sentence, 2 possible completions for the story, and the number - either 1 or 2 - corresponding to the correct completion. Each line contains the following fields:

- `InputStoryid`: text string containing the identifier of the story.
- `InputSentence1`: The first statement in the story.
- `InputSentence2`: The second statement in the story.
- `InputSentence3`: The third statement in the story.
- `InputSentence4`: The forth statement in the story.
- `RandomFifthSentenceQuiz1`: first possible continuation of the story.
- `RandomFifthSentenceQuiz2`: second possible continuation of the story.
- `AnswerRightEnding`: correct possible ending; either 1 or 2.