The Scholarly Question Answering over Linked Data (Scholarly QALD) at The International Semantic Web Conference (ISWC) 2023 challenge presents two sub-tasks to tackle question answering (QA) over knowledge graphs (KGs). We answer the KGQA over DBLP (DBLP-QUAD) task by proposing a neuro-symbolic (NS) framework based on PSYCHIC, an extractive QA model capable of identifying the query and entities related to a KG question. Our system achieved a F1 score of 00.18% on question answering and came in third place for entity linking (EL) with a score of 71.00%.Comment: 10 pages, 3 figures, 2 tables, accepted for the Scholarly-QALD challenge at the International Semantic Web Conference (ISWC) 202
Natural language has long been the most prominent tool for humans to disseminate, learn and create k...
Knowledge graph question answering (KGQA) facilitates information access by leveraging structured da...
Knowledge graphs have gained increasing popularity in the last decade in science and technology. How...
A knowledge-based question answering (KB-QA) system is one that answers natural language questions w...
Question Answering (QA) over Knowledge Graphs (KG) aims to develop a system that is capable of answe...
Question answering (QA) is one of the most important and challenging tasks for understanding human l...
Simple factoid question answering (QA) is a task, where the questions can be answered by looking up ...
In Web search, entity-seeking queries often trigger a special question answering (QA) system. It may...
Knowledge graphs are a powerful concept for querying large amounts of data. These knowledge graphs a...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
A promising pathway for natural language question answering over knowledge graphs (KG-QA) is to tran...
A promising pathway for natural language question answering over knowledge graphs (KG-QA) is to tran...
Answering complex first-order logic (FOL) queries on knowledge graphs is a fundamental task for mult...
Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of...
Natural language has long been the most prominent tool for humans to disseminate, learn and create k...
Knowledge graph question answering (KGQA) facilitates information access by leveraging structured da...
Knowledge graphs have gained increasing popularity in the last decade in science and technology. How...
A knowledge-based question answering (KB-QA) system is one that answers natural language questions w...
Question Answering (QA) over Knowledge Graphs (KG) aims to develop a system that is capable of answe...
Question answering (QA) is one of the most important and challenging tasks for understanding human l...
Simple factoid question answering (QA) is a task, where the questions can be answered by looking up ...
In Web search, entity-seeking queries often trigger a special question answering (QA) system. It may...
Knowledge graphs are a powerful concept for querying large amounts of data. These knowledge graphs a...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
A promising pathway for natural language question answering over knowledge graphs (KG-QA) is to tran...
A promising pathway for natural language question answering over knowledge graphs (KG-QA) is to tran...
Answering complex first-order logic (FOL) queries on knowledge graphs is a fundamental task for mult...
Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of...
Natural language has long been the most prominent tool for humans to disseminate, learn and create k...
Knowledge graph question answering (KGQA) facilitates information access by leveraging structured da...
Knowledge graphs have gained increasing popularity in the last decade in science and technology. How...