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kasunUdayanga/Sinhala_Annotation_Dataset

Sinhala Named Entity Recognition (NER) Dataset - 85,000 Annotations Dataset Description This is a high-quality Named Entity Recognition (NER) dataset for the Sinhala language, consisting of approximately 85,000 annotations. The dataset was manually curated and annotated by a team of three students to support NLP research for low-resource languages. The data is sourced from diverse domains, including social media comments, news articles, and public domain texts… See the full description on the dataset page: https://huggingface.co/datasets/kasunUdayanga/Sinhala_Annotation_Dataset.

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Sinhala Named Entity Recognition (NER) Dataset - 85,000 Annotations

Dataset Description

This is a high-quality Named Entity Recognition (NER) dataset for the Sinhala language, consisting of approximately 85,000 annotations. The dataset was manually curated and annotated by a team of three students to support NLP research for low-resource languages.

The data is sourced from diverse domains, including social media comments, news articles, and public domain texts, capturing the nuances of both formal and informal Sinhala usage.

Annotators & Contact

This dataset was manually annotated and curated by the following students. For inquiries regarding the dataset, please contact:

—[D.D.K.I Udayanga] - [udayangakasu696@gmail.com]
—[S.A.S Kavindya] - [shainikavindya2@gmail.com]
—[K.M.P.S Gunasekara] - [pasindusgkmp@gmail.com]

Dataset Structure

Format

The dataset follows the BIO (Beginning, Inside, Outside) format, commonly used for sequence labeling tasks. Each token is paired with a corresponding tag.

Label Statistics

The distribution of the entities in this dataset is as follows:

Label	Count	Description
B-PER	6,386	Beginning of a Person's name
I-PER	1,744	Inside of a Person's name
B-LOC	4,074	Beginning of a Location
I-LOC	253	Inside of a Location
B-ORG	3,762	Beginning of an Organization
I-ORG	707	Inside of an Organization
B-Other	51,048	Beginning of other entities
I-Other	190	Inside of other entities
O	18,489	Outside (Non-entity words)

Data Example

Each entry consists of a sentence split into tokens with their respective NER tags:

Tag Number (ID)	Tag Label
0	O
1	B-PER
2	I-PER
3	B-LOC
4	I-LOC
5	B-ORG
6	I-ORG
7	B-Other
8	I-Other

Intended Use

—Named Entity Recognition: Training models like BERT, XLM-R, or LSTM-CRF for Sinhala NER.
—Language Modeling: Fine-tuning language models for Sinhala.
—Academic Research: Studying the linguistic patterns of entities in South Asian languages.

Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are free to share and adapt the material as long as appropriate credit is given to the original creators.