File size: 5,091 Bytes
44b6b27 d453029 44b6b27 d453029 44b6b27 |
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": "[Github](https://github.com/lauhaide/clads)",
"paper-bibtext": "```\n@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}\n```",
"paper-url": "https://arxiv.org/abs/2202.09583",
"contact-name": "Laura Perez-Beltrachini",
"contact-email": "[email protected]"
},
"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"
}
}
} |