iMETRE: Incorporating Markers of Entity Types for Relation Extraction
N Harsha Vardhan Manav Chaudhary
Sentence-level relation extraction (RE) aims to identify the relationship
between 2 entities given a contextual sentence. While there have been many
attempts to solve this problem, the current solutions have a lot of room to
improve. In this paper, we approach the task of relationship extraction in the
financial dataset REFinD. Our approach incorporates typed entity markers
representations and various models finetuned on the dataset, which has allowed
us to achieve an F1 score of 69.65% on the validation set. Through this paper,
we discuss various approaches and possible limitations.