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Found 5 papers, 1 papers with code
A Prism Module for Semantic Disentanglement in Name Entity Recognition
To solve this problem, we propose a prism module to disentangle the semantic aspects of words and reduce noise at the input layer of a model.
Ranked #52 on
Named Entity Recognition (NER)
on CoNLL 2003 (English)
Neural Entity Reasoner for Global Consistency in NER
Given an input sentence, the NE-Reasoner layer can infer over multiple entities to increase the global consistency of output labels, which then be transfered into entities for the input of next layer.
Event Identification as a Decision Process with Non-linear Representation of Text
We propose scale-free Identifier Network(sfIN), a novel model for event identification in documents.
Object-oriented Neural Programming (OONP) for Document Understanding
We propose Object-oriented Neural Programming (OONP), a framework for semantically parsing documents in specific domains.
