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README.md
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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:
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## Languages
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## Supported Tasks
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Named Entity Recognition
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## Dataset Usage
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### Using `datasets` library
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```
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### Using `seacrowd` library
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```import seacrowd as sc
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# Load the dataset using the default config
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# Check all available subsets (config names) of the dataset
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# Load the dataset using a specific config
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```
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## Dataset Homepage
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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:
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O (0): Non-entity or other words not falling into the specified categories.
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B-WIS (1): Beginning of a tourism-related entity.
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I-WIS (2): Continuation of a tourism-related entity.
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B-LOC (3): Beginning of a location entity.
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I-LOC (4): Continuation of a location entity.
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B-FAS (5): Beginning of a facility entity.
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I-FAS (6): Continuation of a facility entity.
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## Languages
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## Supported Tasks
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Named Entity Recognition
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## Dataset Usage
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### Using `datasets` library
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```
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from datasets import load_dataset
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dset = datasets.load_dataset("SEACrowd/indoner_tourism", trust_remote_code=True)
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```
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### Using `seacrowd` library
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```import seacrowd as sc
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# Load the dataset using the default config
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dset = sc.load_dataset("indoner_tourism", schema="seacrowd")
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# Check all available subsets (config names) of the dataset
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print(sc.available_config_names("indoner_tourism"))
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# Load the dataset using a specific config
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dset = sc.load_dataset_by_config_name(config_name="<config_name>")
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```
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More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
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## Dataset Homepage
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