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README.md
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- Data_urls: ["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/plenary_full_sentences.jsonl.bz2"]
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## Other files in dataset
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ner_and_ud_manually_annotated_sentences
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Conllu files
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Meta-data files
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[Person](#person) models.
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raw_data
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## Dataset Entities
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* All the dates in the dataset are represented in the format: '%Y-%m-%d %H:%M'
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#### Person
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The Person entity contains the following fields:
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- `person_id`: A unique identifier for the person. For example, "2660". (type: string).
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- `date_of_birth`: The person's date of birth. For example: "1921-03-02 00:00". (type: string).
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- `place_of_birth`: The country the person was born in, mentioned in Hebrew. For example, "ืจืืื ืื". (type: string).
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- `year_of_aliya`: The year the person migrated to Israel if not born there. For example, "1949". Empty if the person was born in Israel or hasn't migrated there. (type: string).
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- `date_of_death`: The date the person died, if not alive. For example, "2000-06-26 00:00". Empty if the person is still alive. (type: string).
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- `mother_tongue`: The person's first language. Currently unavailable. (type: string).
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- `religion`: The person's religion, mentioned in Hebrew. For example "ืืืืื". (type: string).
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- `nationality`: The person's nationality, mentioned in Hebrew. For example "ืืืืื". (type: string).
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`faction_id`, `faction_general_name`, `knesset_faction_id`, `current_faction_name`, `member_of_coalition_or_opposition`, `faction_popular_initials`, `faction_active_periods`, `faction_knesset_numbers`,`faction_coalition_or_opposition_memberships`, `faction_political_orientation`, `faction_other_names`, `faction_notes`, `faction_wiki_link`.
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Please refer to the respective entity section for details on each field.
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## Usage
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#### Option 1: with HuggingFace
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- Data_urls: ["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/plenary_full_sentences.jsonl.bz2"]
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## Other files in dataset
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- `ner_and_ud_manually_annotated_sentences`: contains files with ~4700 manually annotated sentences from the Knesset corpus for the NER and dependencies sentences.
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- `Conllu files`: The morphological fields of the sentences in a conllu format. corresponding to the morphological_fields of the [Sentence](#sentence) model.
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- `Meta-data files`: csv tables containing the details about the factions and the Knesset members in our dataset. corresponding the fields of the [Faction](#faction) and
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[Person](#person) models.
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- `raw_data`: All the original protocols as recieved from the Knesset in .doc, .docx and pdf formats.
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# * All the dates in the dataset are represented in the format: '%Y-%m-%d %H:%M'
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## Dataset Entities
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#### Person
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The Person entity contains the following fields:
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- `person_id`: A unique identifier for the person. For example, "2660". (type: string).
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- `date_of_birth`: The person's date of birth. For example: "1921-03-02 00:00". (type: string).
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- `place_of_birth`: The country the person was born in, mentioned in Hebrew. For example, "ืจืืื ืื". (type: string).
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- `year_of_aliya`: The year the person migrated to Israel if not born there. For example, "1949". Empty if the person was born in Israel or hasn't migrated there. (type: string).
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- `date_of_death`: The date the person died, if not alive. For example, "2000-06-26 00:00". Empty if the person is still alive. (type: string)[*].
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- `mother_tongue`: The person's first language. Currently unavailable. (type: string).
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- `religion`: The person's religion, mentioned in Hebrew. For example "ืืืืื". (type: string).
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- `nationality`: The person's nationality, mentioned in Hebrew. For example "ืืืืื". (type: string).
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`faction_id`, `faction_general_name`, `knesset_faction_id`, `current_faction_name`, `member_of_coalition_or_opposition`, `faction_popular_initials`, `faction_active_periods`, `faction_knesset_numbers`,`faction_coalition_or_opposition_memberships`, `faction_political_orientation`, `faction_other_names`, `faction_notes`, `faction_wiki_link`.
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Please refer to the respective entity section for details on each field.
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## Usage
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#### Option 1: with HuggingFace
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