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    • Peyrard, Maxime (5)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Live blog summarization [<Journal>] Avinesh, P. V. S. [Verfasser]; Peyrard, Maxime [Verfasser]; Meyer, Christian M. [Verfasser] DNB Subject Category Language Show details 2 Better than Average: Paired Evaluation of NLP systems ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Eger, Steffen; Peyrard, Maxime. - : Underline Science Inc., 2021 BASE Show details 3 On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ... Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : arXiv, 2020 BASE Show details 4 On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020 BASE Show details 5 On aligning OpenIE extractions with Knowledge Bases: A case study Gashteovski, Kiril; Gemulla, Rainer; Kotnis, Bhushan; Hertling, Sven; Meilicke, Christian. - : Association for Computational Linguistics (ACL), 2020 Abstract: Open information extraction (OIE) is the task of extracting relations and their corresponding arguments from a natural language text in un- supervised manner. Outputs of such systems are used for downstream tasks such as ques- tion answering and automatic knowledge base (KB) construction. Many of these downstream tasks rely on aligning OIE triples with refer- ence KBs. Such alignments are usually eval- uated w.r.t. a specific downstream task and, to date, no direct manual evaluation of such alignments has been performed. In this paper, we directly evaluate how OIE triples from the OPIEC corpus are related to the DBpedia KB w.r.t. information content. First, we investigate OPIEC triples and DBpedia facts having the same arguments by comparing the information on the OIE surface relation with the KB rela- tion. Second, we evaluate the expressibility of general OPIEC triples in DBpedia. We in- vestigate whether—and, if so, how—a given OIE triple can be mapped to a single KB fact. We found that such mappings are not always possible because the information in the OIE triples tends to be more specific. Our evalua- tion suggests, however, that significant part of OIE triples can be expressed by means of KB formulas instead of individual facts. Keyword: 004 Informatik URL: https://madoc.bib.uni-mannheim.de/61524/1/On%20Aligning%20OpenIE%20Extractions%20with%20Knowledge%20Bases%20A%20Case%20Study.pdf https://madoc.bib.uni-mannheim.de/61524 https://doi.org/10.18653/v1/2020.eval4nlp-1.14 https://madoc.bib.uni-mannheim.de/61524/ BASE Hide details 6 Principled Approaches to Automatic Text Summarization Peyrard, Maxime. - 2019 BASE Show details

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