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f
1
{
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{
            
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  "author": "Jennifer D'Souza and S\u00f6ren Auer and Ted Pedersen",
2
  "author": "Jennifer D'Souza and S\u00f6ren Auer and Ted Pedersen",
            
3
  "author_email": "",
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  "author_email": "",
            
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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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  "extras": [],
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  "extras": [],
            
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  "groups": [],
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  "groups": [],
            
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  "id": "2b92e3fd-1ab8-45bb-995c-6102b5bd2f5f",
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  "id": "2b92e3fd-1ab8-45bb-995c-6102b5bd2f5f",
            
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  "isopen": true,
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  "isopen": true,
            
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  "license_id": "cc-by-sa",
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  "license_id": "cc-by-sa",
            
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  "license_title": "Creative Commons Attribution Share-Alike",
10
  "license_title": "Creative Commons Attribution Share-Alike",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
            
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  "maintainer": "Jennifer D'Souza",
12
  "maintainer": "Jennifer D'Souza",
            
13
  "maintainer_email": "jennifer.dsouza@tib.eu",
13
  "maintainer_email": "jennifer.dsouza@tib.eu",
            
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  "metadata_created": "2021-07-23T07:28:39.166946",
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  "metadata_created": "2021-07-23T07:28:39.166946",
            
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  "metadata_modified": "2021-07-23T07:30:09.835196",
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  "metadata_modified": "2021-07-23T07:31:23.057582",
            
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  "name": "semeval-2021-task-11-shared-task-dataset",
16
  "name": "semeval-2021-task-11-shared-task-dataset",
            
17
  "notes": "NLPContributionGraph - Structuring Scholarly NLP 
17
  "notes": "NLPContributionGraph - Structuring Scholarly NLP 
            
18
Contributions in the Open Research Knowledge 
18
Contributions in the Open Research Knowledge 
            
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Graph\r\n\r\nBackground\r\n\r\nNLPContributionGraph was introduced as 
19
Graph\r\n\r\nBackground\r\n\r\nNLPContributionGraph was introduced as 
            
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Task 11 at SemEval 2021 for the first time. The task is defined on a 
20
Task 11 at SemEval 2021 for the first time. The task is defined on a 
            
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dataset of Natural Language Processing (NLP) scholarly articles with 
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dataset of Natural Language Processing (NLP) scholarly articles with 
            
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their contributions structured to be integrable within Knowledge Graph 
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their contributions structured to be integrable within Knowledge Graph 
            
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infrastructures such as the Open Research Knowledge Graph. The 
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infrastructures such as the Open Research Knowledge Graph. The 
            
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structured contribution annotations are provided as (1) Contribution 
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structured contribution annotations are provided as (1) Contribution 
            
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sentences : a set of sentences about the contribution in the article; 
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sentences : a set of sentences about the contribution in the article; 
            
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(2) Scientific terms and relations: a set of scientific terms and 
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(2) Scientific terms and relations: a set of scientific terms and 
            
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relational cue phrases extracted from the contribution sentences; and 
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relational cue phrases extracted from the contribution sentences; and 
            
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(3) Triples: semantic statements that pair scientific terms with a 
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(3) Triples: semantic statements that pair scientific terms with a 
            
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relation, modeled toward subject-predicate-object RDF statements for 
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relation, modeled toward subject-predicate-object RDF statements for 
            
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KG building. The Triples are organized under three (mandatory) or more 
30
KG building. The Triples are organized under three (mandatory) or more 
            
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of twelve total information units (viz., ResearchProblem, Approach, 
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of twelve total information units (viz., ResearchProblem, Approach, 
            
32
Model, Code, Dataset, ExperimentalSetup, Hyperparameters, Baselines, 
32
Model, Code, Dataset, ExperimentalSetup, Hyperparameters, Baselines, 
            
33
Results, Tasks, Experiments, and AblationAnalysis).\r\n\r\nThe Shared 
33
Results, Tasks, Experiments, and AblationAnalysis).\r\n\r\nThe Shared 
            
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Task\r\n\r\nAs a complete submission for the Shared Task, given NLP 
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Task\r\n\r\nAs a complete submission for the Shared Task, given NLP 
            
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scholarly articles in plaintext format, systems had to automatically 
35
scholarly articles in plaintext format, systems had to automatically 
            
36
extract the following information: contribution sentences; scientific 
36
extract the following information: contribution sentences; scientific 
            
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term and predicate phrases from the sentences; and * 
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term and predicate phrases from the sentences; and * 
            
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(subject,predicate,object) triple statements toward KG building 
38
(subject,predicate,object) triple statements toward KG building 
            
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organized under three or more of twelve total information units.\r\n",
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organized under three or more of twelve total information units.\r\n",
            
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  "num_resources": 1,
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  "num_resources": 2,
            
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  "num_tags": 7,
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  "num_tags": 7,
            
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  "organization": {
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  "organization": {
            
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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 
46
Technology, abbreviated TIB, is the national library of the Federal 
            
47
Republic of Germany for all fields of engineering, technology, and the 
47
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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    "id": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
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    "id": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
            
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    "image_url": 
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    "image_url": 
            
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3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png",
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3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png",
            
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    "is_organization": true,
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    "is_organization": true,
            
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    "name": "tib-iasis",
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    "name": "tib-iasis",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "TIB",
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    "title": "TIB",
            
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    "type": "organization"
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    "type": "organization"
            
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  },
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  },
            
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  "owner_org": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
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  "owner_org": "0c5362f5-b99e-41db-8256-3d0d7549bf4d",
            
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  "private": false,
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  "private": false,
            
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  "relationships_as_object": [],
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  "relationships_as_object": [],
            
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  "relationships_as_subject": [],
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  "relationships_as_subject": [],
            
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  "resources": [
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  "resources": [
            
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    {
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    {
            
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      "cache_last_updated": null,
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      "cache_last_updated": null,
            
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      "cache_url": null,
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      "cache_url": null,
            
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      "created": "2021-07-23T07:30:09.849592",
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      "created": "2021-07-23T07:30:09.849592",
            
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      "datastore_active": false,
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      "datastore_active": false,
            
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      "description": "\r\nTraining Data for the NLPContributionGraph 
68
      "description": "\r\nTraining Data for the NLPContributionGraph 
            
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Shared Task 11 at SemEval-2021\r\n\r\nThe repository is organized as 
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Shared Task 11 at SemEval-2021\r\n\r\nThe repository is organized as 
            
70
follows:\r\n\r\nREADME.md                            
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follows:\r\n\r\nREADME.md                            
            
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\r\n[task-name-folder]/                                # 
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\r\n[task-name-folder]/                                # 
            
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natural_language_inference, paraphrase_generation, question_answering, 
72
natural_language_inference, paraphrase_generation, question_answering, 
            
73
relation_extraction, topic_models\r\n    \u251c\u2500\u2500 
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relation_extraction, topic_models\r\n    \u251c\u2500\u2500 
            
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[article-counter-folder]/                  # ranges between 0 to 100 
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[article-counter-folder]/                  # ranges between 0 to 100 
            
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since we annotated varying numbers of articles per task\r\n    \u2502   
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since we annotated varying numbers of articles per task\r\n    \u2502   
            
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\u251c\u2500\u2500 [articlename].pdf                      # scholarly 
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\u251c\u2500\u2500 [articlename].pdf                      # scholarly 
            
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article pdf\r\n    \u2502   \u251c\u2500\u2500 
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article pdf\r\n    \u2502   \u251c\u2500\u2500 
            
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[articlename]-Grobid-out.txt           # plaintext output from the 
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[articlename]-Grobid-out.txt           # plaintext output from the 
            
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[Grobid parser](https://github.com/kermitt2/grobid)\r\n    \u2502   
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[Grobid parser](https://github.com/kermitt2/grobid)\r\n    \u2502   
            
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\u251c\u2500\u2500 [articlename]-Stanza-out.txt           # plaintext 
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\u251c\u2500\u2500 [articlename]-Stanza-out.txt           # plaintext 
            
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preprocessed output from 
81
preprocessed output from 
            
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[Stanza](https://github.com/stanfordnlp/stanza)\r\n    \u2502   
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[Stanza](https://github.com/stanfordnlp/stanza)\r\n    \u2502   
            
83
\u251c\u2500\u2500 sentences.txt                          # annotated 
83
\u251c\u2500\u2500 sentences.txt                          # annotated 
            
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Contribution sentences in the file\r\n    \u2502   \u251c\u2500\u2500 
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Contribution sentences in the file\r\n    \u2502   \u251c\u2500\u2500 
            
85
entities.txt                           # annotated entities in the 
85
entities.txt                           # annotated entities in the 
            
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Contribution sentences\r\n    \u2502   \u2514\u2500\u2500 info-units/                            
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Contribution sentences\r\n    \u2502   \u2514\u2500\u2500 info-units/                            
            
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# the folder containing information units in JSON format\r\n    \u2502   
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# the folder containing information units in JSON format\r\n    \u2502   
            
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\u2502   \u2514\u2500\u2500 research-problem.json              # 
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\u2502   \u2514\u2500\u2500 research-problem.json              # 
            
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`research problem` mandatory information unit in json format\r\n    
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`research problem` mandatory information unit in json format\r\n    
            
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\u2502   \u2502   \u2514\u2500\u2500 model.json                         
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\u2502   \u2502   \u2514\u2500\u2500 model.json                         
            
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# `model` information unit in json format; in some articles it is 
91
# `model` information unit in json format; in some articles it is 
            
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called `approach`\r\n    \u2502   \u2502   \u2514\u2500\u2500 ...                                
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called `approach`\r\n    \u2502   \u2502   \u2514\u2500\u2500 ...                                
            
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# there are 12 information units in all and each article may be 
93
# there are 12 information units in all and each article may be 
            
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annotated by 3 or 6\r\n    \u2502   \u2514\u2500\u2500 triples/                               
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annotated by 3 or 6\r\n    \u2502   \u2514\u2500\u2500 triples/                               
            
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# the folder containing information unit triples one per line\r\n    
95
# the folder containing information unit triples one per line\r\n    
            
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\u2502   \u2502   \u2514\u2500\u2500 research-problem.txt               
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\u2502   \u2502   \u2514\u2500\u2500 research-problem.txt               
            
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# `research problem` triples (one research problem statement per 
97
# `research problem` triples (one research problem statement per 
            
98
line)\r\n    \u2502   \u2502   \u2514\u2500\u2500 model.txt                          
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line)\r\n    \u2502   \u2502   \u2514\u2500\u2500 model.txt                          
            
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# `model` triples (one statement per line)\r\n    \u2502   \u2502   
99
# `model` triples (one statement per line)\r\n    \u2502   \u2502   
            
100
\u2514\u2500\u2500 ...                                # there are 12 
100
\u2514\u2500\u2500 ...                                # there are 12 
            
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information units in all and each article may be annotated by 3 or 
101
information units in all and each article may be annotated by 3 or 
            
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6\r\n    \u2502   \u2514\u2500\u2500 ...                                    
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6\r\n    \u2502   \u2514\u2500\u2500 ...                                    
            
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# there are between 1 to 100 articles annotated for each task, so this 
103
# there are between 1 to 100 articles annotated for each task, so this 
            
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repeats for the remaining annotated articles\r\n    \u2514\u2500\u2500 
104
repeats for the remaining annotated articles\r\n    \u2514\u2500\u2500 
            
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...                                        # there are 24 tasks 
105
...                                        # there are 24 tasks 
            
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selected overall, so this repeats 23 more times\r\n\r\n",
106
selected overall, so this repeats 23 more times\r\n\r\n",
            
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      "format": "json, pdf, txt",
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      "format": "json, pdf, txt",
            
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      "hash": "",
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      "hash": "",
            
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      "id": "c4c7da41-4bc7-4512-9cba-611c570cf97f",
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      "mimetype": null,
            
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      "mimetype_inner": null,
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      "mimetype_inner": null,
            
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      "name": "Training Dataset",
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      "name": "Training Dataset",
            
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      "package_id": "2b92e3fd-1ab8-45bb-995c-6102b5bd2f5f",
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      "package_id": "2b92e3fd-1ab8-45bb-995c-6102b5bd2f5f",
            
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      "size": null,
            
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      "state": "active",
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      "state": "active",
            
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      "url": "https://github.com/ncg-task/training-data",
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      "url": "https://github.com/ncg-task/training-data",
            
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      "url_type": null
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      "url_type": null
            
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    },
            
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    {
            
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      "cache_last_updated": null,
            
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      "created": "2021-07-23T07:31:23.074109",
            
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      "datastore_active": false,
            
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      "description": "Trial data for the NLPContributionGraph Shared 
            
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Task 11 at SemEval-2021.",
            
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      "format": "json, pdf, txt",
            
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      "hash": "",
            
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      "id": "012f4b52-bdb0-4ed3-8c5b-fd00b9630eae",
            
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      "mimetype": null,
            
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      "name": "Trial Dataset",
            
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      "package_id": "2b92e3fd-1ab8-45bb-995c-6102b5bd2f5f",
            
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    }
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    }
            
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  ],
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  ],
            
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  "state": "draft",
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  "state": "draft",
            
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  "tags": [
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  "tags": [
            
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    {
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    {
            
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      "display_name": "dataset",
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      "display_name": "dataset",
            
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      "id": "ce5ad030-ca3d-47e6-abd1-5c92a2806f1b",
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      "id": "ce5ad030-ca3d-47e6-abd1-5c92a2806f1b",
            
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      "name": "dataset",
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      "name": "dataset",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "language resource",
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      "display_name": "language resource",
            
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      "id": "95e3d7f3-d046-428b-98c7-93653d23a183",
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      "id": "95e3d7f3-d046-428b-98c7-93653d23a183",
            
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      "name": "language resource",
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      "name": "language resource",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
163
    {
            
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      "display_name": "natural language processing",
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      "display_name": "natural language processing",
            
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      "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c",
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      "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c",
            
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      "name": "natural language processing",
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      "name": "natural language processing",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
168
      "vocabulary_id": null
            
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    },
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    },
            
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    {
170
    {
            
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      "display_name": "open research knowledge graph",
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      "display_name": "open research knowledge graph",
            
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      "id": "c9fb26fb-f92f-4740-899e-290c1a384971",
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      "id": "c9fb26fb-f92f-4740-899e-290c1a384971",
            
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      "name": "open research knowledge graph",
173
      "name": "open research knowledge graph",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
175
      "vocabulary_id": null
            
153
    },
176
    },
            
154
    {
177
    {
            
155
      "display_name": "scholarly knowledge graphs",
178
      "display_name": "scholarly knowledge graphs",
            
156
      "id": "759ea23d-8996-4917-b4b5-d020b86f7d1a",
179
      "id": "759ea23d-8996-4917-b4b5-d020b86f7d1a",
            
157
      "name": "scholarly knowledge graphs",
180
      "name": "scholarly knowledge graphs",
            
158
      "state": "active",
181
      "state": "active",
            
159
      "vocabulary_id": null
182
      "vocabulary_id": null
            
160
    },
183
    },
            
161
    {
184
    {
            
162
      "display_name": "semeval",
185
      "display_name": "semeval",
            
163
      "id": "44b579c2-0954-4335-8e31-92288b06eb7e",
186
      "id": "44b579c2-0954-4335-8e31-92288b06eb7e",
            
164
      "name": "semeval",
187
      "name": "semeval",
            
165
      "state": "active",
188
      "state": "active",
            
166
      "vocabulary_id": null
189
      "vocabulary_id": null
            
167
    },
190
    },
            
168
    {
191
    {
            
169
      "display_name": "shared task",
192
      "display_name": "shared task",
            
170
      "id": "ffd2394b-4c6d-4c18-9d24-66e7e851bd2f",
193
      "id": "ffd2394b-4c6d-4c18-9d24-66e7e851bd2f",
            
171
      "name": "shared task",
194
      "name": "shared task",
            
172
      "state": "active",
195
      "state": "active",
            
173
      "vocabulary_id": null
196
      "vocabulary_id": null
            
174
    }
197
    }
            
175
  ],
198
  ],
            
176
  "title": "SemEval-2021 Task 11 Shared Task Dataset",
199
  "title": "SemEval-2021 Task 11 Shared Task Dataset",
            
177
  "type": "dataset",
200
  "type": "dataset",
            
178
  "url": "https://github.com/ncg-task/",
201
  "url": "https://github.com/ncg-task/",
            
179
  "version": "1.0"
202
  "version": "1.0"
            
180
}
203
}