36 citations · 86 across the 22 of their papers we have counts for
26 papers
DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph
Debayan Banerjee, Arefa, Ricardo Usbeck +1
In this work, we present a web application named DBLPLink, which performs entity linking over the DBLP scholarly knowledge graph. DBLPLink uses text-to-text pre-trained language mo…
Biomedical Entity Linking with Triple-aware Pre-Training
Xi Yan, Cedric Möller, Ricardo Usbeck
Linking biomedical entities is an essential aspect in biomedical natural language processing tasks, such as text mining and question answering. However, a difficulty of linking the…
The Role of Output Vocabulary in T2T LMs for SPARQL Semantic Parsing
Debayan Banerjee, Pranav Ajit Nair, Ricardo Usbeck +1
In this work, we analyse the role of output vocabulary for text-to-text (T2T) models on the task of SPARQL semantic parsing. We perform experiments within the the context of knowle…
DBLP-QuAD: A Question Answering Dataset over the DBLP Scholarly Knowledge Graph
Debayan Banerjee, Sushil Awale, Ricardo Usbeck +1
In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DBLP is an on-line reference for bibliographic information on major computer scien…
GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering
Debayan Banerjee, Pranav Ajit Nair, Ricardo Usbeck +1
In this work, we present an end-to-end Knowledge Graph Question Answering (KGQA) system named GETT-QA. GETT-QA uses T5, a popular text-to-text pre-trained language model. The model…
AmQA: Amharic Question Answering Dataset
Tilahun Abedissa, Ricardo Usbeck, Yaregal Assabie
Question Answering (QA) returns concise answers or answer lists from natural language text given a context document. Many resources go into curating QA datasets to advance robust m…