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Joint Model for End-to-End Relation Extraction
Journal
Studies in Computational Intelligence
ISSN
1860949X
Date Issued
2023-01-01
Author(s)
Pawar, Sachin Sharad
Bhattacharyya, Pushpak
Palshikar, Girish Keshav
Abstract
In this chapter, we propose a new approach which combines Neural Networks and Markov Logic Networks to address all the three sub-tasks of end-to-end relation extraction jointly—(i) identifying boundaries of entity mentions, (ii) identifying entity types of these mentions, and (iii) identifying appropriate semantic relation for each pair of mentions. We design the “All Word Pairs” neural network model (AWP-NN) which reduces the solution of the three sub-tasks to predict an appropriate label for each word pair in a given sentence. End-to-end relation extraction output can then be constructed easily from these labels of word pairs.
Volume
1058