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--- |
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language: |
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- pt |
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source_datasets: |
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- assin2 |
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task_categories: |
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- text-classification |
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task_ids: |
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- text-scoring |
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- natural-language-inference |
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- semantic-similarity-scoring |
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--- |
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# Dataset Card for ASSIN 2 (ADA) |
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### Dataset Summary |
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The ASSIN 2 corpus is composed of rather simple sentences. Following the procedures of SemEval 2014 Task 1. |
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The training and validation data are composed, respectively, of 6,500 and 500 sentence pairs in Brazilian Portuguese, |
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annotated for entailment and semantic similarity. Semantic similarity values range from 1 to 5, and text entailment |
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classes are either entailment or none. The test data are composed of approximately 3,000 sentence pairs with the same |
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annotation. All data in the original dataset were manually annotated. |
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This dataset extends the original ASSIN2 adding the `cosine_similarity` column calculated using OpenAI's `text-embedding-ada-002` |
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for research and benchmarking purposes, as it is currently considered one of the best multilingual models for this task. |
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### Languages |
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The language supported is Portuguese. |
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## Dataset Structure |
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### Data Fields |
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- `premise`: a `string` feature. |
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- `hypothesis`: a `string` feature. |
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- `relatedness_score`: a `float32` feature. |
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- `entailment_judgment`: a classification label, with possible values including `NONE`, `ENTAILMENT`. |
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- `ada_cosine_similarity`: the similarity calculated using OpenAI ada v2 embeddings |
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### Data Splits |
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The data is split into train, validation and test set. The split sizes are as follow: |
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| Train | Val | Test | |
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| ------ | ----- | ---- | |
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| 6500 | 500 | 2448 | |
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### Citation Information |
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``` |
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@inproceedings{real2020assin, |
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title={The assin 2 shared task: a quick overview}, |
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author={Real, Livy and Fonseca, Erick and Oliveira, Hugo Goncalo}, |
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booktitle={International Conference on Computational Processing of the Portuguese Language}, |
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pages={406--412}, |
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year={2020}, |
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organization={Springer} |
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} |
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``` |