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{
"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"
}
}
} |