Search Results for author:
Found 4 papers, 3 papers with code
CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild
Existing relation extraction (RE) methods typically focus on extracting relational facts between entity pairs within single sentences or documents.
Coreferential Reasoning Learning for Language Representation
Language representation models such as BERT could effectively capture contextual semantic information from plain text, and have been proved to achieve promising results in lots of downstream NLP tasks with appropriate fine-tuning.
Ranked #31 on
Relation Extraction
on DocRED
Lexical Sememe Prediction using Dictionary Definitions by Capturing Local Semantic Correspondence
We find that sememes of each word are usually semantically matched to different words in its dictionary definition, and we name this matching relationship local semantic correspondence.
Using BERT for Word Sense Disambiguation
Word Sense Disambiguation (WSD), which aims to identify the correct sense of a given polyseme, is a long-standing problem in NLP.
