Document-level Relation Extraction

40 papers with code • 0 benchmarks • 0 datasets

Document-level RE aim to identify the relations of various entity pairs expressed across multiple sentences.


Use these libraries to find Document-level Relation Extraction models and implementations
2 papers

Most implemented papers

DocRED: A Large-Scale Document-Level Relation Extraction Dataset

thunlp/DocRED ACL 2019

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs.

Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction

PaddlePaddle/Research 20 Feb 2021

Our experiments demonstrate the usefulness of the proposed entity structure and the effectiveness of SSAN.

Reasoning with Latent Structure Refinement for Document-Level Relation Extraction

nanguoshun/LSR ACL 2020

Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence entities.

Document-level Relation Extraction as Semantic Segmentation

zjunlp/DocuNet 7 Jun 2021

Specifically, we leverage an encoder module to capture the context information of entities and a U-shaped segmentation module over the image-style feature map to capture global interdependency among triples.

A sequence-to-sequence approach for document-level relation extraction

johngiorgi/seq2rel BioNLP (ACL) 2022

In this paper, we develop a sequence-to-sequence approach, seq2rel, that can learn the subtasks of DocRE (entity extraction, coreference resolution and relation extraction) end-to-end, replacing a pipeline of task-specific components.

Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction

tonytan48/re-docred 25 May 2022

We analyze the causes and effects of the overwhelming false negative problem in the DocRED dataset.

Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs

fenchri/edge-oriented-graph IJCNLP 2019

We thus propose an edge-oriented graph neural model for document-level relation extraction.

Fine-tune Bert for DocRED with Two-step Process

hongwang600/DocRed 26 Sep 2019

Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on the document-level relation extraction.

Improving Document-level Relation Extraction via Contextualizing Mention Representations and Weighting Mention Pairs

nefujiangping/EncAttAgg 9 Aug 2020

However, these models have two shortcomings: (i) they cannot obtain contextualized representations of a mention by low computational cost, when the mention is involved in different entity pairs; (ii) they ignore the different weights for the mention pairs of a target entity pair.

Global-to-Local Neural Networks for Document-Level Relation Extraction

nju-websoft/GLRE EMNLP 2020

Relation extraction (RE) aims to identify the semantic relations between named entities in text.