{ "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": "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" } } }