SEACrowd/indoner_tourism

This dataset is designed for named entity recognition (NER) tasks in the Bahasa Indonesia tourism domain. It contains labeled sequences of named entities, including locations, facilities, and tourism-related entities. The dataset is annotated with the following entity types:

O (0): Non-entity or other words not falling into the specified categories. B-WIS (1): Beginning of a tourism-related entity. I-WIS (2): Continuation of a tourism-related entity. B-LOC (3): Beginning of a location entity. I-LOC (4): Continuation of a location entity. B-FAS (5): Beginning of a facility entity. I-FAS (6): Continuation of a facility entity.

Languages

ind

Supported Tasks

Named Entity Recognition

Dataset Usage

Using datasets library

from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/indoner_tourism", trust_remote_code=True)

Using seacrowd library

# Load the dataset using the default config
dset = sc.load_dataset("indoner_tourism", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("indoner_tourism"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")

More details on how to load the seacrowd library can be found here.

Dataset Homepage

https://github.com/fathanick/IndoNER-Tourism/tree/main

Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

Dataset License

Academic Free License v3.0 (afl-3.0)

Citation

If you are using the Indoner Tourism dataloader in your work, please cite the following:

@article{JLK,
    author = {Ahmad Hidayatullah and Muhammad Fakhri Despawida Aulia Putra and Adityo Permana Wibowo and Kartika Rizqi Nastiti},
    title = { Named Entity Recognition on Tourist Destinations Reviews in the Indonesian Language},
    journal = {Jurnal Linguistik Komputasional},
    volume = {6},
    number = {1},
    year = {2023},
    keywords = {},
    abstract = {To find information about tourist destinations, tourists usually search the reviews about the destinations they want to visit. However, many studies made it hard for them to see the desired information. Named Entity Recognition (NER) is one of the techniques to detect entities in a text. The objective of this research was to make a NER model using BiLSTM to detect and evaluate entities on tourism destination reviews. This research used 2010 reviews of several tourism destinations in Indonesia and chunked them into 116.564 tokens of words. Those tokens were labeled according to their categories: the name of the tourism destination, locations, and facilities. If the tokens could not be classified according to the existing categories, the tokens would be labeled as O (outside). The model has been tested and gives 94,3% as the maximum average of F1-Score.},
    issn = {2621-9336}, pages = {30--35},   doi = {10.26418/jlk.v6i1.89},
    url = {https://inacl.id/journal/index.php/jlk/article/view/89}
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}