32 citations · 36 across the 5 of their papers we have counts for
8 papers
HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri +3
Recently, several Knowledge Graph Embedding (KGE) approaches have been devised to represent entities and relations in dense vector space and employed in downstream tasks such as li…
KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Abhishek Nadgeri, Anson Bastos, Kuldeep Singh +4
We present a novel method for relation extraction (RE) from a single sentence, mapping the sentence and two given entities to a canonical fact in a knowledge graph (KG). Especially…
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata
Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang' +3
In this paper, we propose CHOLAN, a modular approach to target end-to-end entity linking (EL) over knowledge bases. CHOLAN consists of a pipeline of two transformer-based models in…
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh +4
In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG). R…
Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models
Isaiah Onando Mulang', Kuldeep Singh, Chaitali Prabhu +3
Pretrained Transformer models have emerged as state-of-the-art approaches that learn contextual information from text to improve the performance of several NLP tasks. These models,…
From Stock Prediction to Financial Relevance: Repurposing Attention Weights to Assess News Relevance Without Manual Annotations
Luciano Del Corro, Johannes Hoffart
We present a method to automatically identify financially relevant news using stock price movements and news headlines as input. The method repurposes the attention weights of a ne…