Task Categories: text-classification
Languages: tl
Multilinguality: monolingual
Size Categories: 1K<n<10K
Licenses: unknown
Language Creators: crowdsourced
Source Datasets: original

Dataset Card for Dengue Dataset in Filipino

Dataset Summary

Benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets.

Supported Tasks and Leaderboards

[More Information Needed]


The dataset is primarily in Filipino, with the addition of some English words commonly used in Filipino vernacular.

Dataset Structure

Data Instances

Sample data:

  "text": "Tapos ang dami pang lamok.",
  "absent": "0",
  "dengue": "0",
  "health": "0",
  "mosquito": "1",
  "sick": "0"

Data Fields

[More Information Needed]

Data Splits

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]


Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

Jan Christian Cruz

Licensing Information

[More Information Needed]

Citation Information

@INPROCEEDINGS{8459963, author={E. D. {Livelo} and C. {Cheng}}, booktitle={2018 IEEE International Conference on Agents (ICA)}, title={Intelligent Dengue Infoveillance Using Gated Recurrent Neural Learning and Cross-Label Frequencies}, year={2018}, volume={}, number={}, pages={2-7}, doi={10.1109/AGENTS.2018.8459963}} }


Thanks to @anaerobeth for adding this dataset.

Models trained or fine-tuned on dengue_filipino

None yet