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1
{
f
1
{
            
2
  "author": "Jennifer D'Souza",
2
  "author": "Jennifer D'Souza",
            
3
  "author_email": "jennifer.dsouza@tib.eu",
3
  "author_email": "jennifer.dsouza@tib.eu",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/hodc41f5",
5
  "doi": "10.25835/hodc41f5",
            
6
  "doi_date_published": "2022-10-07",
6
  "doi_date_published": "2022-10-07",
            
7
  "doi_publisher": "LUIS",
7
  "doi_publisher": "LUIS",
            
8
  "doi_status": "true",
8
  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
9
  "domain": "https://data.uni-hannover.de",
            
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  "groups": [],
10
  "groups": [],
            
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  "have_copyright": "Yes",
11
  "have_copyright": "Yes",
            
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  "id": "e7e8ca91-d0bb-433b-b1a0-9a92c9477775",
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  "id": "e7e8ca91-d0bb-433b-b1a0-9a92c9477775",
            
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  "isopen": false,
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  "isopen": false,
            
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  "license_id": "CC-BY-SA-3.0",
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  "license_id": "CC-BY-SA-3.0",
            
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  "license_title": "CC-BY-SA-3.0",
15
  "license_title": "CC-BY-SA-3.0",
            
16
  "maintainer": "Jennifer D'Souza",
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  "maintainer": "Jennifer D'Souza",
            
17
  "maintainer_email": "",
17
  "maintainer_email": "",
            
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  "metadata_created": "2023-01-12T13:14:10.784838",
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  "metadata_created": "2023-01-12T13:14:10.784838",
            
n
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  "metadata_modified": "2023-01-12T13:14:10.784844",
n
19
  "metadata_modified": "2023-08-04T08:46:24.834737",
            
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  "name": "luh-cs-ner-dataset",
20
  "name": "luh-cs-ner-dataset",
            
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  "notes": "# Computer Science Named Entity Recognition in the Open 
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  "notes": "# Computer Science Named Entity Recognition in the Open 
            
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Research Knowledge Graph\r\n\r\n### 1) About\r\n\r\nThis work proposes 
22
Research Knowledge Graph\r\n\r\n### 1) About\r\n\r\nThis work proposes 
            
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a standardized CS-NER task by defining a set of seven 
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a standardized CS-NER task by defining a set of seven 
            
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_contribution-centric_ scholarly\r\nentities for CS NER viz., 
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_contribution-centric_ scholarly\r\nentities for CS NER viz., 
            
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_research problem_ , _solution_ , _resource_ , _language_ ,\r\n_tool_ 
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_research problem_ , _solution_ , _resource_ , _language_ ,\r\n_tool_ 
            
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, _method_ , and _dataset_ . \r\n\r\nThe main contributions 
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, _method_ , and _dataset_ . \r\n\r\nThe main contributions 
            
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are:\r\n\r\n1) Merges annotations for contribution-centric named 
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are:\r\n\r\n1) Merges annotations for contribution-centric named 
            
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entities from related work as the following datasets: \r\n   \r\n- The 
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entities from related work as the following datasets: \r\n   \r\n- The 
            
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dataset proposed in [Analyzing the Dynamics of Research by Extracting 
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dataset proposed in [Analyzing the Dynamics of Research by Extracting 
            
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Key Aspects of Scientific Papers](https://aclanthology.org/I11-1001/) 
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Key Aspects of Scientific Papers](https://aclanthology.org/I11-1001/) 
            
31
(Gupta & Manning, IJCNLP 2011) is the source for 
31
(Gupta & Manning, IJCNLP 2011) is the source for 
            
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](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/ftd), 
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](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/ftd), 
            
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annotated for both titles and abstracts for the following select 
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annotated for both titles and abstracts for the following select 
            
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entities mapped to our standardized types _focus_ -> _solution_ ; 
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entities mapped to our standardized types _focus_ -> _solution_ ; 
            
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_domain_ -> _research problem_ ; and _technique_ -> _method_ \r\n   
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_domain_ -> _research problem_ ; and _technique_ -> _method_ \r\n   
            
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\r\n- The dataset proposed in [Multi-Task Identification of Entities, 
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\r\n- The dataset proposed in [Multi-Task Identification of Entities, 
            
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Relations, and Coreference for Scientific Knowledge Graph 
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Relations, and Coreference for Scientific Knowledge Graph 
            
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Construction](https://aclanthology.org/D18-1360/) (Luan et al., EMNLP 
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Construction](https://aclanthology.org/D18-1360/) (Luan et al., EMNLP 
            
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2018) is the source for 
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2018) is the source for 
            
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ttps://github.com/jd-coderepos/contributions-ner-cs/tree/main/scierc), 
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ttps://github.com/jd-coderepos/contributions-ner-cs/tree/main/scierc), 
            
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annotated for abstracts for the following select entities with 
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annotated for abstracts for the following select entities with 
            
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mappings _task_ -> _research problem_\r\n\r\n   - The dataset proposed 
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mappings _task_ -> _research problem_\r\n\r\n   - The dataset proposed 
            
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in [SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly 
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in [SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly 
            
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NLP Contributions for a Research Knowledge 
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NLP Contributions for a Research Knowledge 
            
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Graph](https://aclanthology.org/2021.semeval-1.44/) (D\u2019Souza et 
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Graph](https://aclanthology.org/2021.semeval-1.44/) (D\u2019Souza et 
            
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al., SemEval 2021) is the source for 
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al., SemEval 2021) is the source for 
            
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](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/ncg), 
47
](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/ncg), 
            
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annotated for both titles and abstracts for _research problem_\r\n\r\n   
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annotated for both titles and abstracts for _research problem_\r\n\r\n   
            
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- https://paperswithcode.com/ as the 
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- https://paperswithcode.com/ as the 
            
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c](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/pwc) 
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c](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/pwc) 
            
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annotated for both titles and abstracts for _task_ -> _research 
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annotated for both titles and abstracts for _task_ -> _research 
            
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problem_ and _method_ entities.\r\n\r\n2) Additionally, supplies a new 
52
problem_ and _method_ entities.\r\n\r\n2) Additionally, supplies a new 
            
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annotated dataset for the titles in the ACL anthology in the [acl 
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annotated dataset for the titles in the ACL anthology in the [acl 
            
54
y](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/acl) 
54
y](https://github.com/jd-coderepos/contributions-ner-cs/tree/main/acl) 
            
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\r\nwhere titles are annotated with all seven entities.\r\n\r\n\r\n### 
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\r\nwhere titles are annotated with all seven entities.\r\n\r\n\r\n### 
            
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2) Dataset Statistics for [full 
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2) Dataset Statistics for [full 
            
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d-coderepos/contributions-ner-cs/tree/main/full%20dataset)\r\n\r\n#### 
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d-coderepos/contributions-ner-cs/tree/main/full%20dataset)\r\n\r\n#### 
            
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Titles\r\n\r\n`train.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
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Titles\r\n\r\n`train.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
            
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|\r\n\r\n| solution | 65,213 |\r\n\r\n| research problem | 43,033 
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|\r\n\r\n| solution | 65,213 |\r\n\r\n| research problem | 43,033 
            
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|\r\n\r\n| resource | 19,759 |\r\n\r\n| method | 19,645 |\r\n\r\n| 
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|\r\n\r\n| resource | 19,759 |\r\n\r\n| method | 19,645 |\r\n\r\n| 
            
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tool | 4,856 |\r\n\r\n| dataset | 4,062 |\r\n\r\n| language | 1,704 
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tool | 4,856 |\r\n\r\n| dataset | 4,062 |\r\n\r\n| language | 1,704 
            
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|\r\n\r\n`dev.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
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|\r\n\r\n`dev.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
            
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|\r\n\r\n| solution | 3,685 |\r\n\r\n| research problem | 2,717 
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|\r\n\r\n| solution | 3,685 |\r\n\r\n| research problem | 2,717 
            
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|\r\n\r\n| resource | 1,224 |\r\n\r\n| method | 1,172 |\r\n\r\n| tool 
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|\r\n\r\n| resource | 1,224 |\r\n\r\n| method | 1,172 |\r\n\r\n| tool 
            
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| 264 |\r\n\r\n| dataset | 191 |\r\n\r\n| language | 79 
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| 264 |\r\n\r\n| dataset | 191 |\r\n\r\n| language | 79 
            
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|\r\n\r\n`test.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
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|\r\n\r\n`test.data`\r\n\r\n| NER | Count |\r\n\r\n| --- | --- 
            
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|\r\n\r\n| solution | 29,287 |\r\n\r\n| research problem | 11,093 
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|\r\n\r\n| solution | 29,287 |\r\n\r\n| research problem | 11,093 
            
68
|\r\n\r\n| resource | 8,511 |\r\n\r\n| method | 7,009 |\r\n\r\n| tool 
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|\r\n\r\n| resource | 8,511 |\r\n\r\n| method | 7,009 |\r\n\r\n| tool 
            
69
| 2,272 |\r\n\r\n| dataset | 947 |\r\n\r\n| language | 690 
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| 2,272 |\r\n\r\n| dataset | 947 |\r\n\r\n| language | 690 
            
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|\r\n\r\n\r\n#### Abstracts\r\n\r\n`train-abs.data`\r\n\r\n| NER | 
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|\r\n\r\n\r\n#### Abstracts\r\n\r\n`train-abs.data`\r\n\r\n| NER | 
            
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Count |\r\n\r\n| --- | --- |\r\n\r\n| research problem | 15,498 
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Count |\r\n\r\n| --- | --- |\r\n\r\n| research problem | 15,498 
            
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|\r\n\r\n| method | 12,932 |\r\n\r\n`dev-abs.data`\r\n\r\n| NER | 
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|\r\n\r\n| method | 12,932 |\r\n\r\n`dev-abs.data`\r\n\r\n| NER | 
            
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Count |\r\n\r\n| --- | --- |\r\n\r\n| research problem | 1,450 
73
Count |\r\n\r\n| --- | --- |\r\n\r\n| research problem | 1,450 
            
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|\r\n\r\n| method | 839 |\r\n\r\n`test-abs.data`\r\n\r\n| NER | Count 
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|\r\n\r\n| method | 839 |\r\n\r\n`test-abs.data`\r\n\r\n| NER | Count 
            
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|\r\n\r\n| --- | --- |\r\n\r\n| research problem | 4,123 |\r\n\r\n| 
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|\r\n\r\n| --- | --- |\r\n\r\n| research problem | 4,123 |\r\n\r\n| 
            
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method | 3,170 |\r\n\r\nThe reamining repositories have specialized 
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method | 3,170 |\r\n\r\nThe reamining repositories have specialized 
            
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README files with the respective dataset statistics.\r\n\r\n### 3) 
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README files with the respective dataset statistics.\r\n\r\n### 3) 
            
78
Citation\r\n\r\nAccepted for publication in [ICADL 
78
Citation\r\n\r\nAccepted for publication in [ICADL 
            
79
2022](https://icadl.net/icadl2022/) proceedings.\r\n\r\n`Citation 
79
2022](https://icadl.net/icadl2022/) proceedings.\r\n\r\n`Citation 
            
80
information 
80
information 
            
81
hcoming`\r\n\r\n\r\nPreprint\r\n\r\n```\r\n@article{d2022computer,\r\n  
81
hcoming`\r\n\r\n\r\nPreprint\r\n\r\n```\r\n@article{d2022computer,\r\n  
            
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title={Computer Science Named Entity Recognition in the Open Research 
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title={Computer Science Named Entity Recognition in the Open Research 
            
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Knowledge Graph},\r\n  author={D'Souza, Jennifer and Auer, 
83
Knowledge Graph},\r\n  author={D'Souza, Jennifer and Auer, 
            
84
S{\\\"o}ren},\r\n  journal={arXiv preprint arXiv:2203.14579},\r\n  
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S{\\\"o}ren},\r\n  journal={arXiv preprint arXiv:2203.14579},\r\n  
            
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year={2022}\r\n}\r\n```\r\n\r\n### 4) Additional resources\r\n\r\n#### 
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year={2022}\r\n}\r\n```\r\n\r\n### 4) Additional resources\r\n\r\n#### 
            
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CS NER Software trained on the dataset in this 
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CS NER Software trained on the dataset in this 
            
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repository\r\n\r\nCodebase: 
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repository\r\n\r\nCodebase: 
            
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orkg/nlp/orkg-nlp-experiments/-/tree/master/orkg_cs_ner\r\n\r\nService 
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orkg/nlp/orkg-nlp-experiments/-/tree/master/orkg_cs_ner\r\n\r\nService 
            
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URL - REST API: 
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URL - REST API: 
            
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/docs#/annotation/annotates_paper_annotation_csner_post\r\n\r\nService 
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/docs#/annotation/annotates_paper_annotation_csner_post\r\n\r\nService 
            
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URL - PyPi: 
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URL - PyPi: 
            
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ervices/services.html#cs-ner-computer-science-named-entity-recognition 
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ervices/services.html#cs-ner-computer-science-named-entity-recognition 
            
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\r\n\r\n",
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\r\n\r\n",
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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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 
100
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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  "relationships_as_subject": [],
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  "relationships_as_subject": [],
            
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  "repository_name": "Leibniz University Hannover",
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  "repository_name": "Leibniz University Hannover",
            
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      "name": "CS-NER dataset",
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      "name": "CS-NER dataset",
            
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    {
            
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      "display_name": "information retrieval",
146
      "display_name": "information retrieval",
            
146
      "id": "c094f269-c169-4c66-b2f1-98967cbef543",
147
      "id": "c094f269-c169-4c66-b2f1-98967cbef543",
            
147
      "name": "information retrieval",
148
      "name": "information retrieval",
            
148
      "state": "active",
149
      "state": "active",
            
149
      "vocabulary_id": null
150
      "vocabulary_id": null
            
150
    },
151
    },
            
151
    {
152
    {
            
152
      "display_name": "named entity recognition",
153
      "display_name": "named entity recognition",
            
153
      "id": "2c89c618-a7b7-4d1b-984b-aee05fb83b1e",
154
      "id": "2c89c618-a7b7-4d1b-984b-aee05fb83b1e",
            
154
      "name": "named entity recognition",
155
      "name": "named entity recognition",
            
155
      "state": "active",
156
      "state": "active",
            
156
      "vocabulary_id": null
157
      "vocabulary_id": null
            
157
    },
158
    },
            
158
    {
159
    {
            
159
      "display_name": "natural language processing",
160
      "display_name": "natural language processing",
            
160
      "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c",
161
      "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c",
            
161
      "name": "natural language processing",
162
      "name": "natural language processing",
            
162
      "state": "active",
163
      "state": "active",
            
163
      "vocabulary_id": null
164
      "vocabulary_id": null
            
164
    },
165
    },
            
165
    {
166
    {
            
166
      "display_name": "scientific named entity recognition",
167
      "display_name": "scientific named entity recognition",
            
167
      "id": "7e50bb81-b464-472c-aa9d-25236a2bede2",
168
      "id": "7e50bb81-b464-472c-aa9d-25236a2bede2",
            
168
      "name": "scientific named entity recognition",
169
      "name": "scientific named entity recognition",
            
169
      "state": "active",
170
      "state": "active",
            
170
      "vocabulary_id": null
171
      "vocabulary_id": null
            
171
    }
172
    }
            
172
  ],
173
  ],
            
173
  "terms_of_usage": "Yes",
174
  "terms_of_usage": "Yes",
            
174
  "title": "CS-NER",
175
  "title": "CS-NER",
            
175
  "type": "vdataset",
176
  "type": "vdataset",
            
176
  "url": "https://data.uni-hannover.de/dataset/cs-ner-dataset",
177
  "url": "https://data.uni-hannover.de/dataset/cs-ner-dataset",
            
177
  "version": ""
178
  "version": ""
            
178
}
179
}