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README.md
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num_examples: 997
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download_size: 675236
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dataset_size: 2797070
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---
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# Dataset Card for
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num_examples: 997
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download_size: 675236
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dataset_size: 2797070
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license: apache-2.0
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task_categories:
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- token-classification
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language:
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- gl
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pretty_name: GalicianSRL
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size_categories:
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- 1K<n<10K
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---
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# Dataset Card for GalicianSRL
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Limitations](#limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Citation Information](#citation-information)
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## Dataset Description
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- **Repository:** [GalicianSRL Project Hub](https://github.com/mbruton0426/GalicianSRL)
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- **Paper:** To be updated
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- **Point of Contact:** [Micaella Bruton](mailto:[email protected])
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### Dataset Summary
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The GalicianSRL dataset is a Galician-language dataset of tokenized sentences and the semantic role for each token within a sentence. Semantic roles are limited to verbal roots, argument 0, argument 1, and argument 2. This dataset was created to support the task of semantic role labeling in the Galician language, as no publically available datasets existed as of the date of publication to the contributor's knowledge.
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### Languages
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The text in the dataset is in Galician.
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## Dataset Structure
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### Data Instances
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A typical data point comprises a tokenized sentence, tags for each token, and a sentence id number. An example from the GalicianSRL dataset looks as follows:
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```
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{'tokens': ['O', 'Pleno', 'poderá', ',', 'con', 'todo', ',', 'avocar', 'en', 'calquera', 'momento', 'o', 'debate', 'e', 'votación', 'de', 'calquera', 'proxecto', 'ou', 'proposición', 'de', 'lei', 'que', 'xa', 'fora', 'obxecto', 'de', 'esta', 'delegación', '.'],
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'tags': [0, 1, 4, 0, 0, 0, 0, 17, 0, 0, 16, 0, 15, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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'ids': 504}
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```
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Tags are assigned an id number according to the index of its label as listed in:
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```python
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>>> dataset['train'].features[f"tags"].feature.names
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```
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### Data Fields
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- `tokens`: a list of strings
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- `tags`: a list of integers
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- `ids`: a sentence id, as an integer
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### Data Splits
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The data is split into a training and test set. The final structure and split sizes are as follow:
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```
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DatasetDict({
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train: Dataset({
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features: ['tokens', 'tags', 'ids'],
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num_rows: 1005
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})
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test: Dataset({
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features: ['tokens', 'tags', 'ids'],
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num_rows: 252
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})
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})
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```
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## Dataset Creation
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### Curation Rationale
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GalicianSRL was built to provide a dataset for semantic role labeling in Galician and expand NLP resources available for the Galician language.
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### Source Data
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#### Initial Data Collection and Normalization
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Data was collected from both the [CTG UD annotated corpus](https://github.com/UniversalDependencies/UD_Galician-CTG) and the [TreeGal UD annotated corpus](https://github.com/UniversalDependencies/UD_Galician-TreeGal), and combined to collect the requsite information for this task. For more information, please refer to the publication listed in the citation.
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## Considerations for Using the Data
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### Limitations
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The purpose of this dataset is to help develop a working semantic role labeling system for Galician, as SRL systems have been shown to improve a variety of NLP tasks. It should be noted however that Galician is considered a low-resource language at this time, and as such the dataset has an extrememly limited scope. This dataset would benefit from manual validation of a native speaker of Galician, the inclusion of additional sentences, and an extention of arguments past arg0, arg1, and arg2.
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## Additional Information
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### Dataset Curators
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The dataset was created by Micaella Bruton, as part of her Master's thesis.
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### Citation Information
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```
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@mastersthesis{bruton-galician-srl-23,
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author = {Bruton, Micaella},
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title = {BERTie Bott's Every Flavor Labels: A Tasty Guide to Developing a Semantic Role Labeling Model for Galician},
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school = {Uppsala University},
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year = {2023},
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type = {Master's thesis},
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}
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```
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