3 citations · 6 across the 5 of their papers we have counts for
7 papers
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…
Decoding the Style and Bias of Song Lyrics
Manash Pratim Barman, Amit Awekar, Sambhav Kothari
The central idea of this paper is to gain a deeper understanding of song lyrics computationally. We focus on two aspects: style and biases of song lyrics. All prior works to unders…
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…
It's Only Words And Words Are All I Have
Manash Pratim Barman, Kavish Dahekar, Abhinav Anshuman +1
The central idea of this paper is to demonstrate the strength of lyrics for music mining and natural language processing (NLP) tasks using the distributed representation paradigm.…
Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms
Sweta Agrawal, Amit Awekar
Harassment by cyberbullies is a significant phenomenon on the social media. Existing works for cyberbullying detection have at least one of the following three bottlenecks. First,…
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…