Changes

On December 2, 2024 at 9:44:31 PM UTC, admin:
Updated description of SNLI from
The Stanford Natural Language Inference (SNLI) Corpus is a collection of 570k human-written English sentence pairs supporting the task of natural language inference, predicting whether the premise entails, contradicts, or is neutral with respect to the hypothesis.
to
The dataset used in the paper is the Stanford Natural Language Inference (SNLI) dataset, which consists of 549,367 premise-hypothesis pairs for train/dev/test sets and target labels indicating their relation.
Added the following tags to SNLI
Changed value of field defined_in to https://doi.org/10.48550/arXiv.2203.12942 in SNLI
Changed value of field citation to ['https://doi.org/10.48550/arXiv.2304.04726', 'https://doi.org/10.48550/arXiv.1910.03375', 'https://doi.org/10.48550/arXiv.2406.01647', 'https://doi.org/10.48550/arXiv.2405.06800', 'https://doi.org/10.48550/arXiv.1904.07293', 'https://doi.org/10.48550/arXiv.1904.02464', 'https://doi.org/10.48550/arXiv.2205.06203', 'https://doi.org/10.48550/arXiv.1904.12166', 'https://doi.org/10.48550/arXiv.2103.15429', 'https://doi.org/10.48550/arXiv.1607.04492', 'https://doi.org/10.48550/arXiv.2106.01491', 'https://doi.org/10.48550/arXiv.2012.08012', 'https://doi.org/10.48550/arXiv.1607.06556', 'https://doi.org/10.48550/arXiv.2212.01304', 'https://doi.org/10.48550/arXiv.1812.10814', 'https://doi.org/10.48550/arXiv.1805.11004', 'https://doi.org/10.48550/arXiv.1909.03042', 'https://doi.org/10.48550/arXiv.2202.01279', 'https://doi.org/10.48550/arXiv.2108.12848'] in SNLI
Deleted resource Original Metadata from SNLI
              
    
          
          
        
        
            f 1 { f 1 {
            2   "access_rights": "", 2   "access_rights": "",
            3   "author": "Samuel R. Bowman", 3   "author": "Samuel R. Bowman",
            4   "author_email": "", 4   "author_email": "",
            5   "citation": [ 5   "citation": [
            n 6     "https://doi.org/10.48550/arXiv.1912.03441", n 
            7     "https://doi.org/10.48550/arXiv.2004.04092", 6     "https://doi.org/10.48550/arXiv.2304.04726",
            8     "https://doi.org/10.18653/v1/2020.acl-main.540", 7     "https://doi.org/10.48550/arXiv.1910.03375",
            9     "https://doi.org/10.18653/v1/W19-5045", 8     "https://doi.org/10.48550/arXiv.2406.01647",
            10     "https://doi.org/10.18653/v1/D19-6109", 9     "https://doi.org/10.48550/arXiv.2405.06800",
            11     "https://doi.org/10.48550/arXiv.1904.02181" 10     "https://doi.org/10.48550/arXiv.1904.07293",
            11     "https://doi.org/10.48550/arXiv.1904.02464",
            12     "https://doi.org/10.48550/arXiv.2205.06203",
            13     "https://doi.org/10.48550/arXiv.1904.12166",
            14     "https://doi.org/10.48550/arXiv.2103.15429",
            15     "https://doi.org/10.48550/arXiv.1607.04492",
            16     "https://doi.org/10.48550/arXiv.2106.01491",
            17     "https://doi.org/10.48550/arXiv.2012.08012",
            18     "https://doi.org/10.48550/arXiv.1607.06556",
            19     "https://doi.org/10.48550/arXiv.2212.01304",
            20     "https://doi.org/10.48550/arXiv.1812.10814",
            21     "https://doi.org/10.48550/arXiv.1805.11004",
            22     "https://doi.org/10.48550/arXiv.1909.03042",
            23     "https://doi.org/10.48550/arXiv.2202.01279",
            24     "https://doi.org/10.48550/arXiv.2108.12848"
            12   ], 25   ],
            13   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", 26   "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            n 14   "defined_in": "https://doi.org/10.48550/arXiv.1902.11269", n 27   "defined_in": "https://doi.org/10.48550/arXiv.2203.12942",
            15   "doi": "10.57702/7uuyofll", 28   "doi": "10.57702/7uuyofll",
            16   "doi_date_published": "2024-11-25", 29   "doi_date_published": "2024-11-25",
            17   "doi_publisher": "TIB", 30   "doi_publisher": "TIB",
            18   "doi_status": true, 31   "doi_status": true,
            19   "domain": "https://service.tib.eu/ldmservice", 32   "domain": "https://service.tib.eu/ldmservice",
            20   "extra_authors": [ 33   "extra_authors": [
            21     { 34     {
            22       "extra_author": "Gabor Angeli", 35       "extra_author": "Gabor Angeli",
            23       "orcid": "" 36       "orcid": ""
            24     }, 37     },
            25     { 38     {
            26       "extra_author": "Christopher Potts", 39       "extra_author": "Christopher Potts",
            27       "orcid": "" 40       "orcid": ""
            28     }, 41     },
            29     { 42     {
            30       "extra_author": "Christopher D. Manning", 43       "extra_author": "Christopher D. Manning",
            31       "orcid": "" 44       "orcid": ""
            32     } 45     }
            33   ], 46   ],
            n 34   "groups": [], n 47   "groups": [
            48     {
            49       "description": "",
            50       "display_name": "Natural Language Inference",
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            52       "image_display_url": "",
            53       "name": "natural-language-inference",
            54       "title": "Natural Language Inference"
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            70       "title": "Natural Language Understanding"
            71     },
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            76       "image_display_url": "",
            77       "name": "question-answering",
            78       "title": "Question Answering"
            79     },
            80     {
            81       "description": "",
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            84       "image_display_url": "",
            85       "name": "question-answer-generation",
            86       "title": "Question-Answer Generation"
            87     },
            88     {
            89       "description": "",
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            91       "id": "73e9ec3f-0231-49ed-90ff-171e0a9bcbb5",
            92       "image_display_url": "",
            93       "name": "sentiment-analysis",
            94       "title": "Sentiment Analysis"
            95     },
            96     {
            97       "description": "",
            98       "display_name": "Textual Entailment",
            99       "id": "9b2f3192-e2b1-469d-95bc-790637167139",
            100       "image_display_url": "",
            101       "name": "textual-entailment",
            102       "title": "Textual Entailment"
            103     }
            104   ],
            35   "id": "a96c5c3e-6018-4673-b515-7387a97cb622", 105   "id": "a96c5c3e-6018-4673-b515-7387a97cb622",
            36   "isopen": false, 106   "isopen": false,
            37   "landing_page": "https://nlp.stanford.edu/projects/snli/", 107   "landing_page": "https://nlp.stanford.edu/projects/snli/",
            38   "license_title": null, 108   "license_title": null,
            39   "link_orkg": "", 109   "link_orkg": "",
            40   "metadata_created": "2024-11-25T14:23:48.259221", 110   "metadata_created": "2024-11-25T14:23:48.259221",
            n 41   "metadata_modified": "2024-11-25T14:37:27.895046", n 111   "metadata_modified": "2024-12-02T21:44:30.491933",
            42   "name": "snli", 112   "name": "snli",
            n 43   "notes": "The Stanford Natural Language Inference (SNLI) Corpus is a  n 113   "notes": "The dataset used in the paper is the Stanford Natural 
            44 collection of 570k human-written English sentence pairs supporting the  114 Language Inference (SNLI) dataset, which consists of 549,367 
            45 task of natural language inference, predicting whether the premise  115 premise-hypothesis pairs for train/dev/test sets and target labels 
            46 entails, contradicts, or is neutral with respect to the hypothesis.", 116 indicating their relation.",
            47   "num_resources": 1, 117   "num_resources": 0,
            48   "num_tags": 0, 118   "num_tags": 29,
            49   "organization": { 119   "organization": {
            50     "approval_status": "approved", 120     "approval_status": "approved",
            51     "created": "2024-11-25T12:11:38.292601", 121     "created": "2024-11-25T12:11:38.292601",
            52     "description": "", 122     "description": "",
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            54     "image_url": "", 124     "image_url": "",
            55     "is_organization": true, 125     "is_organization": true,
            56     "name": "no-organization", 126     "name": "no-organization",
            57     "state": "active", 127     "state": "active",
            58     "title": "No Organization", 128     "title": "No Organization",
            59     "type": "organization" 129     "type": "organization"
            60   }, 130   },
            61   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", 131   "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            62   "private": false, 132   "private": false,
            63   "relationships_as_object": [], 133   "relationships_as_object": [],
            64   "relationships_as_subject": [], 134   "relationships_as_subject": [],
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            66     { 136   "services_used_list": "",
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            68       "cache_url": null, 
            69       "created": "2024-11-25T15:30:26", 
            70       "data": [ 
            71         "dcterms:title", 
            72         "dcterms:accessRights", 
            73         "dcterms:creator", 
            74         "dcterms:description", 
            75         "dcterms:issued", 
            76         "dcterms:language", 
            77         "dcterms:identifier", 
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            79         "dcterms:type", 
            80         "dcat:keyword", 
            81         "dcat:landingPage", 
            82         "dcterms:hasVersion", 
            83         "dcterms:format", 
            84         "mls:task", 
            85         "datacite:isDescribedBy" 
            86       ], 
            87       "description": "The json representation of the dataset with its  
            88 distributions based on DCAT.", 
            89       "format": "JSON", 
            90       "hash": "", 
            91       "id": "b8a1c68a-d68c-45e3-86f9-57cad33d15fe", 
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            101       "state": "active", 137   "state": "active",
            102       "url":  138   "tags": [
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            143       "state": "active",
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            145     },
            146     {
            147       "display_name": "Entailment",
            148       "id": "0f5f5eaf-816e-48b5-956a-25345c366f15",
            149       "name": "Entailment",
            150       "state": "active",
            151       "vocabulary_id": null
            152     },
            153     {
            154       "display_name": "NLI",
            155       "id": "2051c5bd-b611-42c1-89a6-9a2fb903869e",
            156       "name": "NLI",
            157       "state": "active",
            158       "vocabulary_id": null
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            160     {
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            192       "state": "active",
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            194     },
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            198       "name": "SNLI",
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            319       "vocabulary_id": null
            320     },
            321     {
            322       "display_name": "sentiment analysis",
            323       "id": "ab481ec4-1a05-4f68-96d7-44beb1d10f63",
            324       "name": "sentiment analysis",
            325       "state": "active",
            326       "vocabulary_id": null
            327     },
            328     {
            329       "display_name": "target labels",
            330       "id": "91854b6c-17c5-44ce-8c2e-4b1bece5f5be",
            331       "name": "target labels",
            332       "state": "active",
            333       "vocabulary_id": null
            334     },
            335     {
            336       "display_name": "text classification",
            337       "id": "98d3b2df-ea96-4826-971b-6c5bf64c999d",
            338       "name": "text classification",
            339       "state": "active",
            340       "vocabulary_id": null
            105     } 341     }
            106   ], 342   ],
            t 107   "services_used_list": "", t 
            108   "state": "active", 
            109   "tags": [], 
            110   "title": "SNLI", 343   "title": "SNLI",
            111   "type": "dataset", 344   "type": "dataset",
            112   "version": "" 345   "version": ""
            113 } 346 }