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title: "Information extraction — papers, page 2"
description: "Information extraction: 76 papers of the Elamur Research library · page 2 of 2 · 26–76, the most cited first."
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# 🔎 Information extraction

76 papers · page 2 of 2 · 26–76 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

Pulling facts out of text: relations, events, attributes and the slots of a record.

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26. [**Relation Extraction: Perspective from Convolutional Neural Networks**Thien Huu Nguyen, Ralph Grishman*2015 · 590 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2015-relation-extraction-perspective-convolutional-neural/)
27. [**Refining Event Extraction through Cross-Document Inference**Heng Ji, Ralph Grishman*2008 · 577 citations*](https://md.research.elamur.ai/free/en/papers/ji-2008-refining-event-extraction-through-cross/)
28. [**Event Detection and Domain Adaptation with Convolutional Neural Networks**Thien Huu Nguyen, Ralph Grishman*2015 · 554 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2015-event-detection-domain-adaptation-convolutional/)
29. [**Cross-Sentence N-ary Relation Extraction with Graph LSTMs**Nanyun Peng, Hoifung Poon, Chris Quirk, et al.*2017 · 553 citations*](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/)
30. [**Using Predicate-Argument Structures for Information Extraction**Mihai Surdeanu, Sanda Harabagiu, John Williams, et al.*2003 · 491 citations*](https://md.research.elamur.ai/free/en/papers/surdeanu-2003-predicate-argument-structures-information-extraction/)
31. [**Exploring Pre-trained Language Models for Event Extraction and Generation**Sen Yang, Dawei Feng, Linbo Qiao, et al.*2019 · 454 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-exploring-pre-trained-language-models/)
32. [**Modeling Joint Entity and Relation Extraction with Table Representation**Makoto Miwa, Yutaka Sasaki*2014 · 443 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2014-modeling-joint-entity-relation-extraction/)
33. [**Entity-Relation Extraction as Multi-Turn Question Answering**Xiaoya Li, Fan Yin, Zijun Sun, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-entity-relation-extraction-as-multi/)
34. [**A general framework for information extraction using dynamic span graphs**Yi Luan, Dave Wadden, Luheng He, et al.*2019 · 427 citations*](https://md.research.elamur.ai/free/en/papers/luan-2019-general-framework-information-extraction-dynamic/)
35. [**Event Extraction as Machine Reading Comprehension**Jian Liu, Yubo Chen, Kang Liu, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-event-extraction-as-machine-reading/)
36. [**Using Document Level Cross-Event Inference to Improve Event Extraction**Shasha Liao, Ralph Grishman*2010 · 407 citations*](https://md.research.elamur.ai/free/en/papers/liao-2010-document-level-cross-event-inference/)
37. [**Entity Disambiguation for Knowledge Base Population**Mark Dredze, Paul McNamee, Delip Rao, et al.*2010 · 394 citations*](https://md.research.elamur.ai/free/en/papers/dredze-2010-entity-disambiguation-knowledge-base-population/)
38. [**Reasoning with Latent Structure Refinement for Document-Level Relation Extraction**Guoshun Nan, Zhijiang Guo, Ivan Sekulic, et al.*2020 · 379 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-reasoning-latent-structure-refinement-document/)
39. [**Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction**Yaojie Lu, Hongyu Lin, Jin Xu, et al.*2021 · 370 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/)
40. [**Question Answering on Freebase via Relation Extraction and Textual Evidence**Kun Xu, Siva Reddy, Yansong Feng, et al.*2016 · 357 citations*](https://md.research.elamur.ai/free/en/papers/xu-2016-question-answering-freebase-relation-extraction/)
41. [**Simple BERT Models for Relation Extraction and Semantic Role Labeling**Peng Shi, Jimmy Lin*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/shi-2019-simple-bert-models-relation-extraction/)
42. [**Using Cross-Entity Inference to Improve Event Extraction**Yu Hong, Jianfeng Zhang, Bin Ma, et al.*2011 · 321 citations*](https://md.research.elamur.ai/free/en/papers/hong-2011-cross-entity-inference-improve-event/)
43. [**Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms**Shulin Liu, Yubo Chen, Kang Liu, et al.*2017 · 309 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-exploiting-argument-information-improve-event/)
44. [**Distant Supervision for Relation Extraction with an Incomplete Knowledge Base**Bonan Min, Ralph Grishman, Li Wan, et al.*2013 · 299 citations*](https://md.research.elamur.ai/free/en/papers/min-2013-distant-supervision-relation-extraction-incomplete/)
45. [**Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger**Massimiliano Ciaramita, Yasemin Altun*2006 · 295 citations*](https://md.research.elamur.ai/free/en/papers/ciaramita-2006-broad-coverage-sense-disambiguation-information/)
46. [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**Jue Wang, Wei Lu*2020 · 286 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/)
47. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT**Xiang Wei; Xingyu Cui; Ning Cheng; Xiaobin Wang; Xin Zhang; Shen Huang; Pengjun Xie; Jinan Xu; Yufeng Chen; Meishan Zhang; Yong Jiang;, Wenjuan Han*2023 · 272 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
48. [**Zero-Shot Transfer Learning for Event Extraction**Lifu Huang, Heng Ji, Kyunghyun Cho, et al.*2018 · 272 citations*](https://md.research.elamur.ai/free/en/papers/huang-2018-zero-shot-transfer-learning-event/)
49. [**MAVEN: A Massive General Domain Event Detection Dataset**Xiaozhi Wang, Ziqi Wang, Xu Han, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-maven-massive-general-domain-event/)
50. [**GPT-RE: In-context Learning for Relation Extraction using Large Language Models**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/)
51. [**Event Extraction as Multi-turn Question Answering**Fayuan Li, Weihua Peng, Yuguang Chen, et al.*2020 · 250 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-event-extraction-as-multi-turn/)
52. [**DEGREE: A Data-Efficient Generation-Based Event Extraction Model**I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, et al.*2022 · 227 citations*](https://md.research.elamur.ai/free/en/papers/hsu-2022-degree-data-efficient-generation-based/)
53. [**A Language-Independent Neural Network for Event Detection**Xiaocheng Feng, Lifu Huang, Duyu Tang, et al.*2016 · 226 citations*](https://md.research.elamur.ai/free/en/papers/feng-2016-language-independent-neural-network-event/)
54. [**SciREX: A Challenge Dataset for Document-Level Information Extraction**Sarthak Jain, Madeleine van Zuylen, Hannaneh Hajishirzi, et al.*2020 · 217 citations*](https://md.research.elamur.ai/free/en/papers/jain-2020-scirex-challenge-dataset-document-level/)
55. [**TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task**Christoph Alt, Aleksandra Gabryszak, Leonhard Hennig*2020 · 212 citations*](https://md.research.elamur.ai/free/en/papers/alt-2020-tacred-revisited-thorough-evaluation-tacred/)
56. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
57. [**Event Detection and Co-reference with Minimal Supervision**Haoruo Peng, Yangqiu Song, Dan Roth*2016 · 180 citations*](https://md.research.elamur.ai/free/en/papers/peng-2016-event-detection-co-reference-minimal/)
58. [**Leveraging FrameNet to Improve Automatic Event Detection**Shulin Liu, Yubo Chen, Shizhu He, et al.*2016 · 163 citations*](https://md.research.elamur.ai/free/en/papers/liu-2016-leveraging-framenet-improve-automatic-event/)
59. [**Event coreference for information extraction**Kevin Humphreys, Robert Gaizauskas, Saliha Azzam*1997 · 116 citations*](https://md.research.elamur.ai/free/en/papers/humphreys-1997-event-coreference-information-extraction/)
60. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
61. [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**Zhanming Jie, Jierui Li, Wei Lu*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jie-2022-learning-reason-deductively-math-word/)
62. [**MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction**Xiaozhi Wang, Yulin Chen, Ning Ding, et al.*2022 · 96 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-maven-ere-unified-large-scale/)
63. [**Probabilistic Coreference in Information Extraction**Andrew Kehler*1997 · 74 citations*](https://md.research.elamur.ai/free/en/papers/kehler-1997-probabilistic-coreference-information-extraction/)
64. [**SinoCoreferencer: An End-to-End Chinese Event Coreference Resolver**Chen Chen, Vincent Ng*2014 · 32 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-sinocoreferencer-end-end-chinese-event/)
65. [**Coreference Resolution for Information Extraction**Dmitry Zelenko, Chinatsu Aone, Jason Tibbetts*2004 · 28 citations*](https://md.research.elamur.ai/free/en/papers/zelenko-2004-coreference-resolution-information-extraction/)
66. [**Event Detection Using Frame-Semantic Parser**Evangelia Spiliopoulou, Eduard Hovy, Teruko Mitamura*2017 · 17 citations*](https://md.research.elamur.ai/free/en/papers/spiliopoulou-2017-event-detection-frame-semantic-parser/)
67. [**Event Extraction from Unstructured Amharic Text**Ephrem Tadesse, Rosa Tsegaye, Kuulaa Qaqqabaa*2020 · 4 citations*](https://md.research.elamur.ai/free/en/papers/tadesse-2020-event-extraction-unstructured-amharic-text/)
68. [**Pragmatic information extraction from subject ellipsis in informal English**Shigeko Nariyama*2006 · 3 citations*](https://md.research.elamur.ai/free/en/papers/nariyama-2006-pragmatic-information-extraction-subject-ellipsis/)
69. [**EPOP: A Benchmark Corpus for Assessing NLP Models on Structured Information Extraction in Plant Health**Claire Nedellec, Marine Courtin, Xinzhi Yao, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nedellec-2026-epop-benchmark-corpus-assessing-nlp/)
70. [**A Novel Synthetic Dataset for Few-Shot Legal Relation Extraction in German**Shiva Banasaz Nouri, Elena Leitner, Julian Moreno-Schneider, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nouri-2026-novel-synthetic-dataset-few-shot/)
71. [**A Study on Building Efficient Zero-Shot Relation Extraction Models**Hugo THOMAS, Caio Corro, Guillaume Gravier, et al.*2026*](https://md.research.elamur.ai/free/en/papers/thomas-2026-study-building-efficient-zero-shot/)
72. [**Benchmarking Portuguese Open Information Extraction**Gabriel Silva, Mário Rodrigues, António Teixeira, et al.*2026*](https://md.research.elamur.ai/free/en/papers/silva-2026-benchmarking-portuguese-open-information-extraction/)
73. [**Do LLMs Use Relational Structure in KG-Grounded Dialogue? Evidence from Entity and Relation Perturbation**Dominic Okonkwo, Ismailcem Budak Arpinar*2026*](https://md.research.elamur.ai/free/en/papers/okonkwo-2026-do-llms-use-relational-structure/)
74. [**Generative Information Extraction from Biographical Sources**Robin Winkle, Manfred Stede, Jörn Kreutel*2026*](https://md.research.elamur.ai/free/en/papers/winkle-2026-generative-information-extraction-biographical-sources/)
75. [**RelEx-PT: A Portuguese Sentence-Level Relation Extraction Dataset**Tomás Pinto, Catarina Silva, Hugo Goncalo Oliveira*2026*](https://md.research.elamur.ai/free/en/papers/pinto-2026-relex-pt-portuguese-sentence-level/)
76. [**Language Model Enhanced Chinese Relation Extraction (基于语言模型增强的中文关系抽取方法)**Ping Xue (薛平), Ying Li (李影), Zhonghai Wu (吴中海)*2023*](https://md.research.elamur.ai/free/en/papers/xue-2023-language-model-enhanced/)

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