activity
20172022
most citedLeveraging Semantic Parsing for Relation Linking over Knowledge Bases

13 citations · 48 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2022★ 8 cited

CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases

Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz +7

Knowledge bases (KBs) are often incomplete and constantly changing in practice. Yet, in many question answering applications coupled with knowledge bases, the sparse nature of KBs…

cs.CL2022★ 7 cited

A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases

Sumit Neelam, Udit Sharma, Hima Karanam +22

Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…

cs.CL2021

A Two-Stage Approach towards Generalization in Knowledge Base Question Answering

Srinivas Ravishankar, June Thai, Ibrahim Abdelaziz +5

Most existing approaches for Knowledge Base Question Answering (KBQA) focus on a specific underlying knowledge base either because of inherent assumptions in the approach, or becau…

cs.CL2021★ 4 cited

SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases

Sumit Neelam, Udit Sharma, Hima Karanam +21

Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…

cs.CL2020★ 9 cited

Leveraging Abstract Meaning Representation for Knowledge Base Question Answering

Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27

Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…

cs.CL2020★ 13 cited

Leveraging Semantic Parsing for Relation Linking over Knowledge Bases

Nandana Mihindukulasooriya, Gaetano Rossiello, Pavan Kapanipathi +6

Knowledgebase question answering systems are heavily dependent on relation extraction and linking modules. However, the task of extracting and linking relations from text to knowle…

cs.AI2017★ 7 cited

Revisiting Simple Neural Networks for Learning Representations of Knowledge Graphs

Srinivas Ravishankar, Chandrahas, Partha Pratim Talukdar

We address the problem of learning vector representations for entities and relations in Knowledge Graphs (KGs) for Knowledge Base Completion (KBC). This problem has received signif…