2 citations · 2 across the 5 of their papers we have counts for
5 papers
Large Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis
Gaurav Negi, MA Waskow, John McCrae +2
Fine-grained opinion analysis of text provides a detailed understanding of expressed sentiments and their targets. Although this level of detail is valuable, annotating opinions in…
Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
Gaurav Negi, Atul Kr. Ojha, Omnia Zayed +1
We propose a scalable method for constructing a temporal opinion knowledge base with large language models (LLMs) as automated annotators. Despite the demonstrated utility of time-…
Towards Semantic Integration of Opinions: Unified Opinion Concepts Ontology and Extraction Task
Gaurav Negi, Dhairya Dalal, Omnia Zayed +1
This paper introduces the Unified Opinion Concepts (UOC) ontology to integrate opinions within their semantic context. The UOC ontology bridges the gap between the semantic represe…
A Hybrid Approach To Aspect Based Sentiment Analysis Using Transfer Learning
Gaurav Negi, Rajdeep Sarkar, Omnia Zayed +1
Aspect-Based Sentiment Analysis (ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. T…
Contextual Modulation for Relation-Level Metaphor Identification
Omnia Zayed, John P. McCrae, Paul Buitelaar
Identifying metaphors in text is very challenging and requires comprehending the underlying comparison. The automation of this cognitive process has gained wide attention lately. H…