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  IndQNER is a NER dataset created by manually annotating the Indonesian translation of Quran text.
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  The dataset contains 18 named entity categories as follow:
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- "Allah": Allah (including synonim of Allah such as Yang maha mengetahui lagi mahabijaksana)
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- "Throne": Throne of Allah (such as 'Arasy)
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- "Artifact": Artifact (such as Ka'bah, Baitullah)
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- "AstronomicalBody": Astronomical body (such as bumi, matahari)
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- "Event": Event (such as hari akhir, kiamat)
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- "HolyBook": Holy book (such as AlQur'an)
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- "Language": Language (such as bahasa Arab
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- "Angel": Angel (such as Jibril, Mikail)
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- "Person": Person (such as Bani Israil, Fir'aun)
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- "Messenger": Messenger (such as Isa, Muhammad, Musa)
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- "Prophet": Prophet (such as Adam, Sulaiman)
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- "AfterlifeLocation": Afterlife location (such as Jahanam, Jahim, Padang Mahsyar)
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- "GeographicalLocation": Geographical location (such as Sinai, negeru Babilonia)
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- "Color": Color (such as kuning tua)
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- "Religion": Religion (such as Islam, Yahudi, Nasrani)
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- "Food": Food (such as manna, salwa)
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  ## Languages
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  ## Supported Tasks
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  Named Entity Recognition
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-
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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/IndQNER", 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("IndQNER", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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- print(sc.available_config_names("IndQNER"))
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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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-
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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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-
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  ## Dataset Homepage
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  IndQNER is a NER dataset created by manually annotating the Indonesian translation of Quran text.
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  The dataset contains 18 named entity categories as follow:
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+ "Allah": Allah (including synonim of Allah such as Yang maha mengetahui lagi mahabijaksana)
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+ "Throne": Throne of Allah (such as 'Arasy)
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+ "Artifact": Artifact (such as Ka'bah, Baitullah)
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+ "AstronomicalBody": Astronomical body (such as bumi, matahari)
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+ "Event": Event (such as hari akhir, kiamat)
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+ "HolyBook": Holy book (such as AlQur'an)
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+ "Language": Language (such as bahasa Arab
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+ "Angel": Angel (such as Jibril, Mikail)
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+ "Person": Person (such as Bani Israil, Fir'aun)
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+ "Messenger": Messenger (such as Isa, Muhammad, Musa)
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+ "Prophet": Prophet (such as Adam, Sulaiman)
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+ "AfterlifeLocation": Afterlife location (such as Jahanam, Jahim, Padang Mahsyar)
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+ "GeographicalLocation": Geographical location (such as Sinai, negeru Babilonia)
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+ "Color": Color (such as kuning tua)
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+ "Religion": Religion (such as Islam, Yahudi, Nasrani)
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+ "Food": Food (such as manna, salwa)
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  ## Languages
 
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  ## Supported Tasks
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  Named Entity Recognition
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+
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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/IndQNER", 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("IndQNER", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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+ print(sc.available_config_names("IndQNER"))
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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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+
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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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+
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  ## Dataset Homepage
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