Changes
On December 16, 2024 at 11:19:51 PM UTC, admin:
-
Changed value of field
doi_status
toTrue
in Semantic Textual Similarity -
Changed value of field
doi_date_published
to2024-12-16
in Semantic Textual Similarity -
Added resource Original Metadata to Semantic Textual Similarity
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2 | "access_rights": "", | 2 | "access_rights": "", | ||
3 | "author": "Eneko Agirre", | 3 | "author": "Eneko Agirre", | ||
4 | "author_email": "", | 4 | "author_email": "", | ||
5 | "citation": [], | 5 | "citation": [], | ||
6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
7 | "defined_in": "https://doi.org/10.48550/arXiv.2105.07623", | 7 | "defined_in": "https://doi.org/10.48550/arXiv.2105.07623", | ||
8 | "doi": "10.57702/38oi5rsy", | 8 | "doi": "10.57702/38oi5rsy", | ||
n | 9 | "doi_date_published": null, | n | 9 | "doi_date_published": "2024-12-16", |
10 | "doi_publisher": "TIB", | 10 | "doi_publisher": "TIB", | ||
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12 | "domain": "https://service.tib.eu/ldmservice", | 12 | "domain": "https://service.tib.eu/ldmservice", | ||
13 | "extra_authors": [ | 13 | "extra_authors": [ | ||
14 | { | 14 | { | ||
15 | "extra_author": "Carmen Banea", | 15 | "extra_author": "Carmen Banea", | ||
16 | "orcid": "" | 16 | "orcid": "" | ||
17 | }, | 17 | }, | ||
18 | { | 18 | { | ||
19 | "extra_author": "Claire Cardie", | 19 | "extra_author": "Claire Cardie", | ||
20 | "orcid": "" | 20 | "orcid": "" | ||
21 | }, | 21 | }, | ||
22 | { | 22 | { | ||
23 | "extra_author": "Daniel Cer", | 23 | "extra_author": "Daniel Cer", | ||
24 | "orcid": "" | 24 | "orcid": "" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "extra_author": "Mona Diab", | 27 | "extra_author": "Mona Diab", | ||
28 | "orcid": "" | 28 | "orcid": "" | ||
29 | }, | 29 | }, | ||
30 | { | 30 | { | ||
31 | "extra_author": "Aitor Gonzalez-Agirre", | 31 | "extra_author": "Aitor Gonzalez-Agirre", | ||
32 | "orcid": "" | 32 | "orcid": "" | ||
33 | }, | 33 | }, | ||
34 | { | 34 | { | ||
35 | "extra_author": "Weiwei Guo", | 35 | "extra_author": "Weiwei Guo", | ||
36 | "orcid": "" | 36 | "orcid": "" | ||
37 | }, | 37 | }, | ||
38 | { | 38 | { | ||
39 | "extra_author": "Rada Mihalcea", | 39 | "extra_author": "Rada Mihalcea", | ||
40 | "orcid": "" | 40 | "orcid": "" | ||
41 | }, | 41 | }, | ||
42 | { | 42 | { | ||
43 | "extra_author": "German Rigau", | 43 | "extra_author": "German Rigau", | ||
44 | "orcid": "" | 44 | "orcid": "" | ||
45 | }, | 45 | }, | ||
46 | { | 46 | { | ||
47 | "extra_author": "Janyce Wiebe", | 47 | "extra_author": "Janyce Wiebe", | ||
48 | "orcid": "" | 48 | "orcid": "" | ||
49 | } | 49 | } | ||
50 | ], | 50 | ], | ||
51 | "groups": [ | 51 | "groups": [ | ||
52 | { | 52 | { | ||
53 | "description": "", | 53 | "description": "", | ||
54 | "display_name": "Text Analysis", | 54 | "display_name": "Text Analysis", | ||
55 | "id": "c6e4118d-2ceb-49cc-97b8-1ddd4db9ffaa", | 55 | "id": "c6e4118d-2ceb-49cc-97b8-1ddd4db9ffaa", | ||
56 | "image_display_url": "", | 56 | "image_display_url": "", | ||
57 | "name": "text-analysis", | 57 | "name": "text-analysis", | ||
58 | "title": "Text Analysis" | 58 | "title": "Text Analysis" | ||
59 | } | 59 | } | ||
60 | ], | 60 | ], | ||
61 | "id": "8a333c88-10a0-43d7-a006-902583c2aa42", | 61 | "id": "8a333c88-10a0-43d7-a006-902583c2aa42", | ||
62 | "isopen": false, | 62 | "isopen": false, | ||
63 | "landing_page": "https://www.aclweb.org/anthology/S17-1025", | 63 | "landing_page": "https://www.aclweb.org/anthology/S17-1025", | ||
64 | "license_title": null, | 64 | "license_title": null, | ||
65 | "link_orkg": "", | 65 | "link_orkg": "", | ||
66 | "metadata_created": "2024-12-16T23:19:49.458258", | 66 | "metadata_created": "2024-12-16T23:19:49.458258", | ||
n | 67 | "metadata_modified": "2024-12-16T23:19:49.458263", | n | 67 | "metadata_modified": "2024-12-16T23:19:50.022822", |
68 | "name": "semantic-textual-similarity", | 68 | "name": "semantic-textual-similarity", | ||
69 | "notes": "The STS benchmark (Cer et al., 2017) and SICK-Relatedness | 69 | "notes": "The STS benchmark (Cer et al., 2017) and SICK-Relatedness | ||
70 | dataset (Marelli et al., 2014) respectively contain 8.6K and 9.8K | 70 | dataset (Marelli et al., 2014) respectively contain 8.6K and 9.8K | ||
71 | labeled sentence pairs, the sizes of which are usually | 71 | labeled sentence pairs, the sizes of which are usually | ||
72 | insuf\ufb01cient for training deep neural networks.", | 72 | insuf\ufb01cient for training deep neural networks.", | ||
n | 73 | "num_resources": 0, | n | 73 | "num_resources": 1, |
74 | "num_tags": 3, | 74 | "num_tags": 3, | ||
75 | "organization": { | 75 | "organization": { | ||
76 | "approval_status": "approved", | 76 | "approval_status": "approved", | ||
77 | "created": "2024-11-25T12:11:38.292601", | 77 | "created": "2024-11-25T12:11:38.292601", | ||
78 | "description": "", | 78 | "description": "", | ||
79 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 79 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
80 | "image_url": "", | 80 | "image_url": "", | ||
81 | "is_organization": true, | 81 | "is_organization": true, | ||
82 | "name": "no-organization", | 82 | "name": "no-organization", | ||
83 | "state": "active", | 83 | "state": "active", | ||
84 | "title": "No Organization", | 84 | "title": "No Organization", | ||
85 | "type": "organization" | 85 | "type": "organization" | ||
86 | }, | 86 | }, | ||
87 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 87 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
88 | "private": false, | 88 | "private": false, | ||
89 | "relationships_as_object": [], | 89 | "relationships_as_object": [], | ||
90 | "relationships_as_subject": [], | 90 | "relationships_as_subject": [], | ||
t | 91 | "resources": [], | t | 91 | "resources": [ |
92 | { | ||||
93 | "cache_last_updated": null, | ||||
94 | "cache_url": null, | ||||
95 | "created": "2024-12-16T23:37:10", | ||||
96 | "data": [ | ||||
97 | "dcterms:title", | ||||
98 | "dcterms:accessRights", | ||||
99 | "dcterms:creator", | ||||
100 | "dcterms:description", | ||||
101 | "dcterms:issued", | ||||
102 | "dcterms:language", | ||||
103 | "dcterms:identifier", | ||||
104 | "dcat:theme", | ||||
105 | "dcterms:type", | ||||
106 | "dcat:keyword", | ||||
107 | "dcat:landingPage", | ||||
108 | "dcterms:hasVersion", | ||||
109 | "dcterms:format", | ||||
110 | "mls:task", | ||||
111 | "datacite:isDescribedBy" | ||||
112 | ], | ||||
113 | "description": "The json representation of the dataset with its | ||||
114 | distributions based on DCAT.", | ||||
115 | "format": "JSON", | ||||
116 | "hash": "", | ||||
117 | "id": "fd18538d-84c7-4c05-b0b3-df445b60120f", | ||||
118 | "last_modified": "2024-12-16T23:19:50.015398", | ||||
119 | "metadata_modified": "2024-12-16T23:19:50.025802", | ||||
120 | "mimetype": "application/json", | ||||
121 | "mimetype_inner": null, | ||||
122 | "name": "Original Metadata", | ||||
123 | "package_id": "8a333c88-10a0-43d7-a006-902583c2aa42", | ||||
124 | "position": 0, | ||||
125 | "resource_type": null, | ||||
126 | "size": 998, | ||||
127 | "state": "active", | ||||
128 | "url": | ||||
129 | resource/fd18538d-84c7-4c05-b0b3-df445b60120f/download/metadata.json", | ||||
130 | "url_type": "upload" | ||||
131 | } | ||||
132 | ], | ||||
92 | "services_used_list": "", | 133 | "services_used_list": "", | ||
93 | "state": "active", | 134 | "state": "active", | ||
94 | "tags": [ | 135 | "tags": [ | ||
95 | { | 136 | { | ||
96 | "display_name": "natural language processing", | 137 | "display_name": "natural language processing", | ||
97 | "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c", | 138 | "id": "8af9c93a-1d87-41e0-83d9-f5d01a2bbd0c", | ||
98 | "name": "natural language processing", | 139 | "name": "natural language processing", | ||
99 | "state": "active", | 140 | "state": "active", | ||
100 | "vocabulary_id": null | 141 | "vocabulary_id": null | ||
101 | }, | 142 | }, | ||
102 | { | 143 | { | ||
103 | "display_name": "sentence similarity", | 144 | "display_name": "sentence similarity", | ||
104 | "id": "6fcf4537-880f-46cf-8edd-a1196b93b39e", | 145 | "id": "6fcf4537-880f-46cf-8edd-a1196b93b39e", | ||
105 | "name": "sentence similarity", | 146 | "name": "sentence similarity", | ||
106 | "state": "active", | 147 | "state": "active", | ||
107 | "vocabulary_id": null | 148 | "vocabulary_id": null | ||
108 | }, | 149 | }, | ||
109 | { | 150 | { | ||
110 | "display_name": "text analysis", | 151 | "display_name": "text analysis", | ||
111 | "id": "8dede2ad-b59f-4a39-b2b2-4259c7ebcaea", | 152 | "id": "8dede2ad-b59f-4a39-b2b2-4259c7ebcaea", | ||
112 | "name": "text analysis", | 153 | "name": "text analysis", | ||
113 | "state": "active", | 154 | "state": "active", | ||
114 | "vocabulary_id": null | 155 | "vocabulary_id": null | ||
115 | } | 156 | } | ||
116 | ], | 157 | ], | ||
117 | "title": "Semantic Textual Similarity", | 158 | "title": "Semantic Textual Similarity", | ||
118 | "type": "dataset", | 159 | "type": "dataset", | ||
119 | "version": "" | 160 | "version": "" | ||
120 | } | 161 | } |