NSTL国家科技图书文献中心

1. A Type Fusion and Span Relation Enhanced Event Extraction Framework for Confused Event NSTL国家科技图书文献中心

Fanshen Meng | Rongheng Lin - 《Database Systems for Advanced Applications,Part II》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 357～372 - 共16页

摘要：Event extraction (EE) is a crucial aspect of | novel event* extraction model which employs type fusion* | Confused events for Event* Extraction named as ONCEE* | . Evaluation results on public event* extraction datasets* | in our approach to event* extraction. The average F1*

关键词： Information extraction | Event extraction | Confused event

2. Multi-layer Sequence Labeling-Based Joint Biomedical Event Extraction NSTL国家科技图书文献中心

Gongchi Chen | Pengchao Wu ... - 《Natural Language Processing and Chinese Computing,Part II》 - CCF International Conference on Natural Language Processing and Chinese Computing - 2025, - 135～148 - 共14页

摘要：In recent years, biomedical event extraction | biomedical event* extraction. MLSL does not introduce prior* | superiority of MLSL in terms of extraction* performance* | has been dominated by complicated pipeline and joint | methods, which need to be simplified. In addition

关键词： Biomedical event extraction | Sequence labeling | Natural language processing

3. COfEE: A comprehensive ontology for event extraction from text NSTL国家科技图书文献中心

Ali Balali | Masoud Asadpour ... - 《Computer speech & language》 - 2025,89(Jan.) - 101702.1～101702.27 - 共27页

摘要： gold-standard data for event* extraction, we present a* | practitioners have turned to Information Extraction* (IE* | ) methods. One of the most challenging IE tasks is Event | Extraction (EE), which involves extracting information | few decades, various event* ontologies, such as ACE*

关键词： Information extraction | Event extraction | Event ontology | Deep learning | Persian language | Online media monitoring

4. MLEE: Event Extraction as Multi-label Classification Task at Token Level NSTL国家科技图书文献中心

Jinshun Yang | Shuangxi Huang ... - 《Intelligence science V》 - International conference on intelligence science - 2025, - 55～65 - 共11页

摘要：Event Extraction is an important task in | , which models Event* Extraction task as Multi-Label* | event trigger of pre-defined event types and their | extraction task in a joint paradigm, can help solving | , pushing trigger extraction* F1 to 85.03% (+4.45*

关键词： Event extraction | pre-trained language model

5. LAAP: Learning the Argument of An Entity with Event Prompts for document-level event extraction NSTL国家科技图书文献中心

Xu J. | Kang X.... - 《Neurocomputing》 - 2025,613(Jan.14) - 1.1～1.11 - 共11页

摘要： Extraction (DEE) aims to identify event types within a | © 2024 Elsevier B.V.Document-level Event | extraction, DEE requires handling events and arguments | Event Prompts (LAAP), which constructs event prompts | placeholders to elicit event-specific information

关键词： Deep learning | Event extraction | Information extraction | Information retrieval | Natural Language Processing

6. Stream mining with integrity constraint learning for event extraction in evolving data streams NSTL国家科技图书文献中心

Calvo Martinez, John | Wobcke, Wayne - 《Knowledge and information systems》 - 2025,67(3) - 2595～2618 - 共24页

摘要： instruments. The problem of event* extraction is to identify* | -layered stream mining method for event* extraction, where* | than event extraction baselines on the event | extraction task and on the subtasks of event detection and | An event* is a structured interaction of*

关键词： Event extraction | Stream mining | Computational social science | Text mining

7. A Multifocal Graph-Based Neural Network Scheme for Topic Event Extraction NSTL国家科技图书文献中心

QIZHI WAN | CHANGXUAN WAN ... - 《ACM transactions on information systems》 - 2025,43(1) - 13.1～13.36 - 共36页

摘要：Event extraction is a long-standing and | been carefully investigated is whether an event* topic* | extracted events. This article formulates the topic event | extraction problem, aiming to identify a representative | event from extracted ones. Specifically, after

关键词： Event Topic | topic event extraction | event graphs | subgraph | graph neural network

8. Event extraction based on self-data augmentation with large language models NSTL国家科技图书文献中心

Yang, Lishan | Fan, Xi ... - 《Memetic computing》 - 2025,17(1) - 共15页

摘要：Event extraction plays a crucial role in | . However, traditional event* extraction methodologies* | and event* extraction. By dynamically assessing and* | accurate and reliable extraction* outcomes.* | natural language processing (NLP), facilitating the

关键词： Event extraction | Data augmentation | Large language models | Logical Thoughts for Self-Data Augmentation (LoTSA)

9. S2D: Enhancing Zero-Shot Cross-Lingual Event Argument Extraction with Semantic Knowledge NSTL国家科技图书文献中心

Zongkai Zhao | Xiuhua Li ... - 《Natural Language Processing and Chinese Computing,Part I》 - CCF International Conference on Natural Language Processing and Chinese Computing - 2025, - 353～365 - 共13页

摘要： event. Some prior works point out that syntactic | Zero-shot Cross-lingual EAE has garnered | significant interests from the community because it could | minimize the need for extensive data annotation to | identify the roles of the arguments within a specific

关键词： Event extraction | Cross lingual | Semantic knowledge

10. Prompt Debiasing via Causal Intervention for Event Argument Extraction NSTL国家科技图书文献中心

Jiaju Lin | Jie Zhou ... - 《Natural Language Processing and Chinese Computing,Part II》 - CCF International Conference on Natural Language Processing and Chinese Computing - 2025, - 96～108 - 共13页

摘要： popular among information extraction tasks (e.g., event | exceed its counterpart in event argument extraction | argument extraction), especially in low-data scenarios | Prompt-based methods have become increasingly | . By formatting a fine-tuning task into a pre

摘要：Event extraction (EE) is a crucial aspect of | novel event* extraction model which employs type fusion* | Confused events for Event* Extraction named as ONCEE* | . Evaluation results on public event* extraction datasets* | in our approach to event* extraction. The average F1*

关键词： Information extraction | Event extraction | Confused event

摘要：In recent years, biomedical event extraction | biomedical event* extraction. MLSL does not introduce prior* | superiority of MLSL in terms of extraction* performance* | has been dominated by complicated pipeline and joint | methods, which need to be simplified. In addition

关键词： Biomedical event extraction | Sequence labeling | Natural language processing

摘要： gold-standard data for event* extraction, we present a* | practitioners have turned to Information Extraction* (IE* | ) methods. One of the most challenging IE tasks is Event | Extraction (EE), which involves extracting information | few decades, various event* ontologies, such as ACE*

关键词： Information extraction | Event extraction | Event ontology | Deep learning | Persian language | Online media monitoring

摘要：Event Extraction is an important task in | , which models Event* Extraction task as Multi-Label* | event trigger of pre-defined event types and their | extraction task in a joint paradigm, can help solving | , pushing trigger extraction* F1 to 85.03% (+4.45*

关键词： Event extraction | pre-trained language model

摘要： Extraction (DEE) aims to identify event types within a | © 2024 Elsevier B.V.Document-level Event | extraction, DEE requires handling events and arguments | Event Prompts (LAAP), which constructs event prompts | placeholders to elicit event-specific information

关键词： Deep learning | Event extraction | Information extraction | Information retrieval | Natural Language Processing

摘要： instruments. The problem of event* extraction is to identify* | -layered stream mining method for event* extraction, where* | than event extraction baselines on the event | extraction task and on the subtasks of event detection and | An event* is a structured interaction of*

关键词： Event extraction | Stream mining | Computational social science | Text mining

摘要：Event extraction is a long-standing and | been carefully investigated is whether an event* topic* | extracted events. This article formulates the topic event | extraction problem, aiming to identify a representative | event from extracted ones. Specifically, after

关键词： Event Topic | topic event extraction | event graphs | subgraph | graph neural network

摘要：Event extraction plays a crucial role in | . However, traditional event* extraction methodologies* | and event* extraction. By dynamically assessing and* | accurate and reliable extraction* outcomes.* | natural language processing (NLP), facilitating the

关键词： Event extraction | Data augmentation | Large language models | Logical Thoughts for Self-Data Augmentation (LoTSA)

摘要： event. Some prior works point out that syntactic | Zero-shot Cross-lingual EAE has garnered | significant interests from the community because it could | minimize the need for extensive data annotation to | identify the roles of the arguments within a specific

关键词： Event extraction | Cross lingual | Semantic knowledge

摘要： popular among information extraction tasks (e.g., event | exceed its counterpart in event argument extraction | argument extraction), especially in low-data scenarios | Prompt-based methods have become increasingly | . By formatting a fine-tuning task into a pre

关键词： Event argument extraction | Prompt learning | Causal intervention

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Event extraction (EE) is a crucial aspect of | novel event extraction model which employs type fusion | Confused events for Event Extraction named as ONCEE | . Evaluation results on public event extraction datasets | in our approach to event extraction. The average F1

关键词： Information extraction | Event extraction | Confused event

摘要：In recent years, biomedical event extraction | biomedical event extraction. MLSL does not introduce prior | superiority of MLSL in terms of extraction performance | has been dominated by complicated pipeline and joint | methods, which need to be simplified. In addition

关键词： Biomedical event extraction | Sequence labeling | Natural language processing

摘要： gold-standard data for event extraction, we present a | practitioners have turned to Information Extraction (IE | ) methods. One of the most challenging IE tasks is Event | Extraction (EE), which involves extracting information | few decades, various event ontologies, such as ACE

关键词： Information extraction | Event extraction | Event ontology | Deep learning | Persian language | Online media monitoring

摘要：Event Extraction is an important task in | , which models Event Extraction task as Multi-Label | event trigger of pre-defined event types and their | extraction task in a joint paradigm, can help solving | , pushing trigger extraction F1 to 85.03% (+4.45

关键词： Event extraction | pre-trained language model

摘要： Extraction (DEE) aims to identify event types within a | © 2024 Elsevier B.V.Document-level Event | extraction, DEE requires handling events and arguments | Event Prompts (LAAP), which constructs event prompts | placeholders to elicit event-specific information

关键词： Deep learning | Event extraction | Information extraction | Information retrieval | Natural Language Processing

摘要： instruments. The problem of event extraction is to identify | -layered stream mining method for event extraction, where | than event extraction baselines on the event | extraction task and on the subtasks of event detection and | An event is a structured interaction of

关键词： Event extraction | Stream mining | Computational social science | Text mining

摘要：Event extraction is a long-standing and | been carefully investigated is whether an event topic | extracted events. This article formulates the topic event | extraction problem, aiming to identify a representative | event from extracted ones. Specifically, after

关键词： Event Topic | topic event extraction | event graphs | subgraph | graph neural network

摘要：Event extraction plays a crucial role in | . However, traditional event extraction methodologies | and event extraction. By dynamically assessing and | accurate and reliable extraction outcomes. | natural language processing (NLP), facilitating the

关键词： Event extraction | Data augmentation | Large language models | Logical Thoughts for Self-Data Augmentation (LoTSA)

摘要： event. Some prior works point out that syntactic | Zero-shot Cross-lingual EAE has garnered | significant interests from the community because it could | minimize the need for extensive data annotation to | identify the roles of the arguments within a specific

关键词： Event extraction | Cross lingual | Semantic knowledge

摘要： popular among information extraction tasks (e.g., event | exceed its counterpart in event argument extraction | argument extraction), especially in low-data scenarios | Prompt-based methods have become increasingly | . By formatting a fine-tuning task into a pre

关键词： Event argument extraction | Prompt learning | Causal intervention

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Event extraction (EE) is a crucial aspect of | novel event* extraction model which employs type fusion* | Confused events for Event* Extraction named as ONCEE* | . Evaluation results on public event* extraction datasets* | in our approach to event* extraction. The average F1*

摘要：In recent years, biomedical event extraction | biomedical event* extraction. MLSL does not introduce prior* | superiority of MLSL in terms of extraction* performance* | has been dominated by complicated pipeline and joint | methods, which need to be simplified. In addition

摘要： gold-standard data for event* extraction, we present a* | practitioners have turned to Information Extraction* (IE* | ) methods. One of the most challenging IE tasks is Event | Extraction (EE), which involves extracting information | few decades, various event* ontologies, such as ACE*

摘要：Event Extraction is an important task in | , which models Event* Extraction task as Multi-Label* | event trigger of pre-defined event types and their | extraction task in a joint paradigm, can help solving | , pushing trigger extraction* F1 to 85.03% (+4.45*

摘要： instruments. The problem of event* extraction is to identify* | -layered stream mining method for event* extraction, where* | than event extraction baselines on the event | extraction task and on the subtasks of event detection and | An event* is a structured interaction of*

摘要：Event extraction is a long-standing and | been carefully investigated is whether an event* topic* | extracted events. This article formulates the topic event | extraction problem, aiming to identify a representative | event from extracted ones. Specifically, after

摘要：Event extraction plays a crucial role in | . However, traditional event* extraction methodologies* | and event* extraction. By dynamically assessing and* | accurate and reliable extraction* outcomes.* | natural language processing (NLP), facilitating the