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  "author": "Moussab Hrou",
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  "author": "Moussab Hrou",
            
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  "author_email": "",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/blecbkwf",
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  "doi": "10.25835/blecbkwf",
            
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  "doi_date_published": "2022-11-01",
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  "doi_date_published": "2022-11-01",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
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  "domain": "https://data.uni-hannover.de",
            
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  "groups": [],
            
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  "have_copyright": "Yes",
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  "have_copyright": "Yes",
            
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  "id": "d5201779-9cd0-4cb1-a323-f9c71ca0d7cd",
            
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  "isopen": false,
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  "license_id": "CC-BY-3.0",
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  "license_id": "CC-BY-3.0",
            
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  "license_title": "CC-BY-3.0",
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  "license_title": "CC-BY-3.0",
            
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  "maintainer": "Moussab Hrou",
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  "maintainer": "Moussab Hrou",
            
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  "maintainer_email": "",
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  "maintainer_email": "",
            
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  "metadata_modified": "2023-08-04T08:46:28.662620",
            
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  "name": 
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  "name": 
            
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-question-answering-for-the-open-research-knowledge-graph-completion",
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-question-answering-for-the-open-research-knowledge-graph-completion",
            
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  "notes": "This dataset is part of the bachelor thesis \"Evaluating 
22
  "notes": "This dataset is part of the bachelor thesis \"Evaluating 
            
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SQuAD-based Question Answering for the Open Research Knowledge Graph 
23
SQuAD-based Question Answering for the Open Research Knowledge Graph 
            
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Completion\". It was created for the finetuning of Bert Based models 
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Completion\". It was created for the finetuning of Bert Based models 
            
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pre-trained on the SQUaD dataset. The Dataset was created using 
25
pre-trained on the SQUaD dataset. The Dataset was created using 
            
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semi-automatic approach on the ORKG data.\r\n\r\nThe dataset.csv file 
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semi-automatic approach on the ORKG data.\r\n\r\nThe dataset.csv file 
            
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contains the entire data (all properties) in a tabular for and is 
27
contains the entire data (all properties) in a tabular for and is 
            
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unsplit. The json files contain only the necessary fields for training 
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unsplit. The json files contain only the necessary fields for training 
            
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and evaluation, with additional fields (index of start and end of the 
29
and evaluation, with additional fields (index of start and end of the 
            
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answers in the abstracts). The data in the json files is split 
30
answers in the abstracts). The data in the json files is split 
            
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(training data)\r\nand evaluation data. We create 4 variants of the 
31
(training data)\r\nand evaluation data. We create 4 variants of the 
            
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training and evaluation sets for each one of the question labels (\"no 
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training and evaluation sets for each one of the question labels (\"no 
            
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label\", \"how\", \"what\", \"which\")\r\n\r\nFor detailed information 
33
label\", \"how\", \"what\", \"which\")\r\n\r\nFor detailed information 
            
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on each of the fields in the dataset, refer to section 4.2 (Corpus) of 
34
on each of the fields in the dataset, refer to section 4.2 (Corpus) of 
            
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the Thesis document that can be found in 
35
the Thesis document that can be found in 
            
36
https://www.repo.uni-hannover.de/handle/123456789/12958.\r\n\r\nThe 
36
https://www.repo.uni-hannover.de/handle/123456789/12958.\r\n\r\nThe 
            
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script used to generate the dataset can be found in the public 
37
script used to generate the dataset can be found in the public 
            
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repository https://github.com/as18cia/thesis_work\r\nand 
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repository https://github.com/as18cia/thesis_work\r\nand 
            
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ver/orkg/nlp/experiments/orkg-fine-tuning-squad-based-models\r\n\r\n",
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ver/orkg/nlp/experiments/orkg-fine-tuning-squad-based-models\r\n\r\n",
            
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    "created": "2017-11-23T17:30:37.757128",
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    "created": "2017-11-23T17:30:37.757128",
            
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    "description": "The German National Library of Science and 
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    "description": "The German National Library of Science and 
            
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Technology, abbreviated TIB, is the national library of the Federal 
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Technology, abbreviated TIB, is the national library of the Federal 
            
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Republic of Germany for all fields of engineering, technology, and the 
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Republic of Germany for all fields of engineering, technology, and the 
            
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natural sciences.",
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natural sciences.",
            
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Research Knowledge Graph Completion",
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