Document-level Event Extraction
14 papers with code • 1 benchmarks • 1 datasets
Libraries
Use these libraries to find Document-level Event Extraction models and implementations
ChFinAnn
Most implemented papers
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction
dolphin-zs/Doc2EDAG
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IJCNLP 2019
Most existing event extraction (EE) methods merely extract event arguments within the sentence scope.
Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker
RunxinXu/GIT
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ACL 2021
Existing methods are not effective due to two challenges of this task: a) the target event arguments are scattered across sentences; b) the correlation among events in a document is non-trivial to model.
Document-level Event Extraction via Parallel Prediction Networks
hangyang-nlp/de-ppn
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ACL 2021
We argue that sentence-level extractors are ill-suited to the DEE task where event arguments always scatter across sentences and multiple events may co-exist in a document.
Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding
xinyadu/doc_event_role
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ACL 2020
Few works in the literature of event extraction have gone beyond individual sentences to make extraction decisions.
Document-Level Event Argument Extraction by Conditional Generation
raspberryice/gen-arg
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NAACL 2021
On the task of argument extraction, we achieve an absolute gain of 7. 6% F1 and 5. 7% F1 over the next best model on the RAMS and WikiEvents datasets respectively.
An Effective System for Multi-format Information Extraction
neukg/MultiIE
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Finally, our system ranks No. 4 on the test set leader-board of this multi-format information extraction task, and its F1 scores for the subtasks of relation extraction, event extractions of sentence-level and document-level are 79. 887%, 85. 179%, and 70. 828% respectively.
Exploiting Data Characteristics for Document-level Event Extraction
coszeros/cab
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ACL ARR November 2021
Document-level event extraction (DEE) extracts structured information of events from a document.
Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph
Spico197/DocEE
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Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference.
A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction
pkunlp-icler/tsar
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NAACL 2022
In this paper, we focus on extracting event arguments from an entire document, which mainly faces two critical problems: a) the long-distance dependency between trigger and arguments over sentences; b) the distracting context towards an event in the document.
RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction
TencentYoutuResearch/EventExtraction-RAAT
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NAACL 2022
To further leverage relation information, we introduce a separate event relation prediction task and adopt multi-task learning method to explicitly enhance event extraction performance.
