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--- |
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size_categories: |
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- 1M<n<10M |
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language: |
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- de |
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- en |
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- es |
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- fr |
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multilinguality: |
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- multilingual |
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task_categories: |
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- token-classification |
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configs: |
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- config_name: German |
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data_files: |
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- split: train |
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path: "data/DiS-ReX/german.txt" |
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- config_name: English |
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data_files: |
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- split: train |
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path: "data/DiS-ReX/english.txt" |
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- config_name: French |
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data_files: |
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- split: train |
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path: "data/DiS-ReX/french.txt" |
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- config_name: Spanish |
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data_files: |
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- split: train |
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path: "data/DiS-ReX/spanish.txt" |
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--- |
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> [!NOTE] |
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> Dataset origin: https://github.com/dair-iitd/DiS-ReX |
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# DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction |
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DiS-ReX, a multilingual dataset for distantly supervised relation extraction. The dataset has over 1.5 million instances, spanning 4 languages (English, Spanish, German and French). Our dataset has 36 positive relation types + 1 no relation (NA) class. |
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# Format |
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The dataset folder has 5 text files |
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``` |
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english.txt |
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german.txt |
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french.txt |
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spanish.txt |
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rel2id.txt |
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``` |
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For files named `<language>.txt`, each line is a unique instance represented as a Python dictionary. An example is shown below: |
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``` |
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{"token": ["at", "the", "58th", "annual", "grammy", "awards", "in", "february", "the", "eagles", "joined", "by", "leadon", "touring", "guitarist", "steuart", "smith", "and", "co-writer", "jackson", "browne", "performed", "\"take", "it", "easy\"", "in", "honor", "of", "frey"], "h": {"name": "steuart smith", "id": "Q3498822", "pos": [15, 17]}, "t": {"name": "eagles", "id": "Q2092297", "pos": [9, 10]}, "relation": "http://dbpedia.org/ontology/associatedBand"} |
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``` |
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Here the keys and values have the following meaning: |
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1. token: A list representing the context sentence. Every element in the list represents a word. |
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2. h: A dictionary for head entity. has the following keys: |
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- name: name of the head |
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- entityid: wikidata id for the entity |
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- pos: a tuple of the form [start index, end index] according to head entity's positition in the token list |
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3. t: A dictionary for tail entity. has the following keys: |
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- name: name of the tail |
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- entityid: wikidata id for the entity |
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- pos: a tuple of the form [start index, end index] according to tail entity's positition in the token list |
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4. relation: relation for the tuple (head entity, tail entity) |
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The dataset format is same as presented in [OpenNRE](https://github.com/thunlp/OpenNRE). For a bag with more than one possible relations, the instances are repeated with a different value for the relation key. An example is shown below: |
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``` |
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{"token": ["huxley", "who", "had", "twice", "visited", "the", "soviet", "union", "was", "originally", "not", "anti-communist", "but", "the", "ruthless", "adoption", "of", "lysenkoism", "by", "joseph", "stalin", "ended", "his", "tolerant", "attitude"], "h": {"name": "joseph stalin", "id": "Q855", "pos": [19, 21]}, "t": {"name": "the soviet union", "id": "Q15180", "pos": [5, 8]}, "relation": "http://dbpedia.org/ontology/country"} |
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{"token": ["huxley", "who", "had", "twice", "visited", "the", "soviet", "union", "was", "originally", "not", "anti-communist", "but", "the", "ruthless", "adoption", "of", "lysenkoism", "by", "joseph", "stalin", "ended", "his", "tolerant", "attitude"], "h": {"name": "joseph stalin", "id": "Q855", "pos": [19, 21]}, "t": {"name": "the soviet union", "id": "Q15180", "pos": [5, 8]}, "relation": "http://dbpedia.org/ontology/deathPlace"} |
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``` |
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The file named `rel2id.txt` contains relation types and the corresponding indices we use during training our model. |
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# Cite |
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The dataset is a part of the pre-print [DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction](https://arxiv.org/abs/2104.08655). We also release our baseline results using mBERT+Bag Attention and present it in our paper. If you use or extend our work, please cite the following paper: |
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``` |
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@misc{bhartiya2021disrex, |
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title={DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction}, |
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author={Abhyuday Bhartiya and Kartikeya Badola and Mausam}, |
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year={2021}, |
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eprint={2104.08655}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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