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DataFunSummit
DataFunSummit
Oct 2, 2021 · Artificial Intelligence

Joint Entity and Relation Extraction: Methods and Document‑Level Approaches

This presentation reviews the importance of entity‑relation extraction for knowledge‑graph construction, compares sentence‑level and complex contexts, and surveys joint extraction techniques—including sequence labeling, table filling, and seq2seq models—as well as document‑level graph‑based methods and future research directions.

Graph Neural NetworksNLPdocument-level
0 likes · 15 min read
Joint Entity and Relation Extraction: Methods and Document‑Level Approaches
DataFunTalk
DataFunTalk
Jul 22, 2021 · Artificial Intelligence

Joint Entity and Relation Extraction: Methods, Challenges, and Document‑Level Approaches

This article reviews the fundamentals of entity‑relation extraction, surveys joint extraction techniques such as sequence labeling, table‑filling and seq2seq models, discusses document‑level graph‑based methods, highlights experimental findings, and outlines future research directions in knowledge‑graph construction.

Graph Neural NetworksNLPdocument-level
0 likes · 17 min read
Joint Entity and Relation Extraction: Methods, Challenges, and Document‑Level Approaches