OpenCeres: When Open Information Extraction Meets the Semi-Structured Web (N19-1)
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| Challenge: | Open Information Extraction (OpenIE) is a problem of extracting triples from natural language text whose predicate relations are not aligned to any pre-defined ontology. |
| Approach: | They propose an open-source method to extract triples from semi-structured websites . they use a semi-supervised label propagation technique to create training data for relations . |
| Outcome: | The proposed method extracts over 2 million triples from 31 websites in the movie vertical. |
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| Challenge: | Existing closed IE datasets are built using Wikipedia, but they have limitations when applied to web domains. |
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Bhushan Kotnis, Kiril Gashteovski, Daniel Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence
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| Challenge: | Open Information Extraction (OpenIE) aims to generate structured tuples from unstructured open-domain text. |
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| Challenge: | Open information extraction (OIE) is the task of extracting facts from natural language text. |
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| Challenge: | Existing methods for knowledge extraction and alignment are limited in quality and performance. |
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| Challenge: | Open Information Extraction (OIE) methods extract facts in the form of triples . ambiguity of these triples hinders their downstream usage . |
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| Challenge: | a tutorial explores the commonalities in the challenges and solutions developed to address information extraction from the World Wide Web. |
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LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction (2021.eacl-main)
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| Challenge: | Open Information Extraction (OIE) systems extract factual propositions into n-ary tuples . current datasets are limited in size and diversity . |
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ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages (2020.acl-main)
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| Challenge: | Existing work on information extraction from semi-structured websites has relied on manual data annotation and learning a model specific to a given template. |
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A Survey on Open Information Extraction from Rule-based Model to Large Language Model (2024.findings-emnlp)
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Liu Pai, Wenyang Gao, Wenjie Dong, Lin Ai, Ziwei Gong, Songfang Huang, Li Zongsheng, Ehsan Hoque, Julia Hirschberg, Yue Zhang
| Challenge: | Open Information Extraction (OpenIE) is a key NLP task aimed at extracting structured information from unstructured text sources. |
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