3 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Noise in Relation Classification Dataset TACRED: Characterization and Reduction
Akshay Parekh, Ashish Anand, Amit Awekar
The overarching objective of this paper is two-fold. First, to explore model-based approaches to characterize the primary cause of the noise. in the RE dataset TACRED Second, to id…
Taxonomical hierarchy of canonicalized relations from multiple Knowledge Bases
Akshay Parekh, Ashish Anand, Amit Awekar
This work addresses two important questions pertinent to Relation Extraction (RE). First, what are all possible relations that could exist between any two given entity types? Secon…
Fine-grained Entity Recognition with Reduced False Negatives and Large Type Coverage
Abhishek Abhishek, Sanya Bathla Taneja, Garima Malik +2
Fine-grained Entity Recognition (FgER) is the task of detecting and classifying entity mentions to a large set of types spanning diverse domains such as biomedical, finance and spo…
Fine-Grained Entity Type Classification by Jointly Learning Representations and Label Embeddings
Abhishek, Ashish Anand, Amit Awekar
Fine-grained entity type classification (FETC) is the task of classifying an entity mention to a broad set of types. Distant supervision paradigm is extensively used to generate tr…