Relationship extraction is the task of extracting semantic relationships from a text. Extracted relationships usually occur between two or more entities of a certain type (e.g. Person, Organisation, Location) and fall into a number of semantic categories (e.g. married to, employed by, lives in).
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In this paper, we propose RESIDE, a distantly-supervised neural relation extraction method which utilizes additional side information from KBs for improved relation extraction.
Relation extraction is the problem of classifying the relationship between two entities in a given sentence.
#2 best model for Relationship Extraction (Distant Supervised) on New York Times Corpus
Semi-supervised bootstrapping techniques for relationship extraction from text iteratively expand a set of initial seed instances.