Results 1 to 10 of about 12,045,326 (363)

GenIE: Generative Information Extraction [PDF]

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
Structured and grounded representation of text is typically formalized by closed information extraction, the problem of extracting an exhaustive set of (subject, relation, object) triplets that are consistent with a predefined set of entities and ...
Martin Josifoski, Nicola De Cao, Maxime Peyrard, Robert West   +3 more
semanticscholar   +5 more sources

Structured information extraction from scientific text with large language models. [PDF]

Nat Commun
Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models
Dagdelen J, Dunn A, Lee S, Walker N, Rosen AS, Ceder G, Persson KA, Jain A.   +7 more
europepmc   +2 more sources

A Survey of Information Extraction Based on Deep Learning

Applied Sciences, 2022
As a core task and an important link in the fields of natural language understanding and information retrieval, information extraction (IE) can structure and semanticize unstructured multi-modal information.
Yang Yang, Zhilei Wu, Yuexiang Yang, Shuangshuang Lian, Fengjie Guo, Zhiwei Wang   +5 more
doaj   +2 more sources

Span-Oriented Information Extraction -- A Unifying Perspective on Information Extraction [PDF]

arXiv
Information Extraction refers to a collection of tasks within Natural Language Processing (NLP) that identifies sub-sequences within text and their labels. These tasks have been used for many years to link extract relevant information and to link free text to structured data.
Ding, Yifan, Yankoski, Michael, Weninger, Tim   +2 more
arxiv   +3 more sources

Neural Open Information Extraction [PDF]

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2018
Conventional Open Information Extraction (Open IE) systems are usually built on hand-crafted patterns from other NLP tools such as syntactic parsing, yet they face problems of error propagation. In this paper, we propose a neural Open IE approach with an
Lei Cui, Furu Wei, M. Zhou
semanticscholar   +5 more sources

Unified Structure Generation for Universal Information Extraction [PDF]

Annual Meeting of the Association for Computational Linguistics, 2022
Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas. In this paper, we propose a unified text-to-structure generation framework, namely UIE, which can universally model different IE tasks ...
Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu   +7 more
semanticscholar   +1 more source

Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness [PDF]

arXiv.org, 2023
The capability of Large Language Models (LLMs) like ChatGPT to comprehend user intent and provide reasonable responses has made them extremely popular lately.
Bo Li, Gexiang Fang, Yang Yang, Quansen Wang, Wei Ye, Wen Zhao, Shikun Zhang   +6 more
semanticscholar   +1 more source

Technological scheme of the combined geothermal-hydrocarbon system for the production and storage of energy resources [PDF]

E3S Web of Conferences, 2021
The complex researches of schemes of extraction and storage of hydrocarbons and geothermal energy are executed in the work. In particular, according to the location, logistics and nature of the processes of generation, transportation, evacuation ...
Fyk Mykhailo I., Biletskyi Volodymyr S., Abbood Majid H., Fyk Oleksandr I.   +3 more
doaj   +1 more source

InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction [PDF]

arXiv.org, 2023
Large language models have unlocked strong multi-task capabilities from reading instructive prompts. However, recent studies have shown that existing large models still have difficulty with information extraction tasks.
Xiao Wang, Wei Zhou, Can Zu, Han Xia, Tianze Chen, Yuan Zhang, Rui Zheng, Junjie Ye, Qi Zhang, Tao Gui, Jihua Kang, J. Yang, Siyuan Li, Chunsai Du   +13 more
semanticscholar   +1 more source

Frequent Pattern Retrieval on Data Streams by using Sliding Window [PDF]

EAI Endorsed Transactions on Energy Web, 2021
In different applications like recommender frameworks and market examination, regular patterns play a significant role in useful mining data. Mining regular patterns from sliding windows over streaming information has become a complex task.
P. Kumar, P. Rao
doaj   +1 more source