Datasets:
GEM
/

Modalities:
Text
ArXiv:
Tags:
License:
File size: 5,072 Bytes
feb9c1e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
{
  "overview": {
    "what": {
      "dataset": "The XWikis Corpus provides datasets with different language pairs and directions for cross-lingual  and multi-lingual abstractive document summarisation. "
    },
    "where": {
      "has-leaderboard": "no",
      "leaderboard-url": "N/A",
      "leaderboard-description": "N/A",
      "website": "https://github.com/lauhaide/clads",
      "paper-bibtext": "@InProceedings{clads-emnlp,\n  author =      \"Laura Perez-Beltrachini and Mirella Lapata\",\n  title =       \"Models and Datasets for Cross-Lingual Summarisation\",\n  booktitle =   \"Proceedings of The 2021 Conference on Empirical Methods in Natural Language Processing \",\n  year =        \"2021\",\n  address =     \"Punta Cana, Dominican Republic\",\n}",
      "paper-url": "https://arxiv.org/abs/2202.09583",
      "contact-name": "Laura Perez-Beltrachini",
      "contact-email": "lperez@ed.ac.uk"
    },
    "languages": {
      "is-multilingual": "yes",
      "license": "cc-by-sa-4.0: Creative Commons Attribution Share Alike 4.0 International",
      "task-other": "N/A",
      "language-names": [
        "German",
        "English",
        "French",
        "Czech"
      ],
      "intended-use": "Cross-lingual and Multi-lingual single long input document abstractive summarisation.",
      "license-other": "N/A",
      "task": "Summarization",
      "communicative": "Entity descriptive summarisation, that is, generate a summary that conveys the most salient facts of a document related to a given entity."
    },
    "credit": {
      "organization-type": [
        "academic"
      ],
      "creators": "Laura Perez-Beltrachini (University of Edinburgh)",
      "gem-added-by": "Laura Perez-Beltrachini (University of Edinburgh) and Ronald Cardenas (University of Edinburgh)"
    },
    "structure": {
      "structure-splits": "For each language pair and direction there exists a train/valid/test split. \nThe test split is a sample of size 7k from the intersection of titles existing in the four languages (cs,fr,en,de).\nTrain/valid are randomly split."
    }
  },
  "curation": {
    "original": {
      "is-aggregated": "no",
      "aggregated-sources": "N/A"
    },
    "language": {
      "found": [
        "Single website"
      ],
      "crowdsourced": [],
      "created": "N/A",
      "machine-generated": "N/A",
      "validated": "other",
      "is-filtered": "not filtered",
      "filtered-criteria": "N/A",
      "obtained": [
        "Found"
      ]
    },
    "annotations": {
      "origin": "found",
      "rater-number": "N/A",
      "rater-qualifications": "N/A",
      "rater-training-num": "N/A",
      "rater-test-num": "N/A",
      "rater-annotation-service-bool": "no",
      "rater-annotation-service": [],
      "values": "The input documents have section structure information.",
      "quality-control": "validated by another rater",
      "quality-control-details": "Bilingual annotators assessed the content overlap of source document and target summaries."
    },
    "consent": {
      "has-consent": "no",
      "consent-policy": "N/A",
      "consent-other": "N/A"
    },
    "pii": {
      "has-pii": "no PII",
      "no-pii-justification": "N/A",
      "is-pii-identified": "N/A",
      "pii-identified-method": "N/A",
      "is-pii-replaced": "N/A",
      "pii-replaced-method": "N/A",
      "pii-categories": []
    },
    "maintenance": {
      "has-maintenance": "no",
      "description": "N/A",
      "contact": "N/A",
      "contestation-mechanism": "N/A",
      "contestation-link": "N/A",
      "contestation-description": "N/A"
    }
  },
  "gem": {
    "rationale": {
      "sole-task-dataset": "no",
      "sole-language-task-dataset": "N/A",
      "distinction-description": "N/A"
    },
    "curation": {
      "has-additional-curation": "no",
      "modification-types": [],
      "modification-description": "N/A",
      "has-additional-splits": "no",
      "additional-splits-description": "N/A",
      "additional-splits-capacicites": "N/A"
    },
    "starting": {}
  },
  "results": {
    "results": {
      "other-metrics-definitions": "N/A",
      "has-previous-results": "yes",
      "current-evaluation": "ROUGE-1/2/L",
      "previous-results": "N/A",
      "model-abilities": "- identification of entity salient information\n- translation\n- multi-linguality\n- cross-lingual transfer, zero-shot, few-shot",
      "metrics": [
        "ROUGE"
      ]
    }
  },
  "considerations": {
    "pii": {},
    "licenses": {
      "dataset-restrictions-other": "N/A",
      "data-copyright-other": "N/A",
      "dataset-restrictions": [
        "public domain"
      ],
      "data-copyright": [
        "public domain"
      ]
    },
    "limitations": {}
  },
  "context": {
    "previous": {
      "is-deployed": "no",
      "described-risks": "N/A",
      "changes-from-observation": "N/A"
    },
    "underserved": {
      "helps-underserved": "no",
      "underserved-description": "N/A"
    },
    "biases": {
      "has-biases": "no",
      "bias-analyses": "N/A"
    }
  }
}