65 citations · 121 across the 16 of their papers we have counts for
7 papers · 1 filter
PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction
Rajdeep Mukherjee, Tapas Nayak, Yash Butala +2
Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinio…
Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise Filtering
Tapas Nayak, Navonil Majumder, Soujanya Poria
Distantly supervised models are very popular for relation extraction since we can obtain a large amount of training data using the distant supervision method without human annotati…
A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents
Tapas Nayak, Hwee Tou Ng
Distantly supervised datasets for relation extraction mostly focus on sentence-level extraction, and they cover very few relations. In this work, we propose cross-document relation…
RTE: A Tool for Annotating Relation Triplets from Text
Ankan Mullick, Animesh Bera, Tapas Nayak
In this work, we present a Web-based annotation tool `Relation Triplets Extractor' \footnote{https://abera87.github.io/annotate/} (RTE) for annotating relation triplets from the te…
Aspect Sentiment Triplet Extraction Using Reinforcement Learning
Samson Yu Bai Jian, Tapas Nayak, Navonil Majumder +1
Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting triplets of aspect terms, their associated sentiments, and the opinion terms that provide evidence for the expr…
Deep Neural Networks for Relation Extraction
Tapas Nayak
Relation extraction from text is an important task for automatic knowledge base population. In this thesis, we first propose a syntax-focused multi-factor attention network model f…