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20152024
most citedIntroduction to Neural Network based Approaches for Question Answering over Knowledge Graphs

42 citations · 101 across the 19 of their papers we have counts for

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cs.CL2024

MATTER: Memory-Augmented Transformer Using Heterogeneous Knowledge Sources

Dongkyu Lee, Chandana Satya Prakash, Jack FitzGerald +1

Leveraging external knowledge is crucial for achieving high performance in knowledge-intensive tasks, such as question answering. The retrieve-and-read approach is widely adopted f…

cs.CL2024

REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking

Nacime Bouziani, Shubhi Tyagi, Joseph Fisher +2

Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE). Howe…

cs.CL20221 cited

An Answer Verbalization Dataset for Conversational Question Answerings over Knowledge Graphs

Endri Kacupaj, Kuldeep Singh, Maria Maleshkova +1

We introduce a new dataset for conversational question answering over Knowledge Graphs (KGs) with verbalized answers. Question answering over KGs is currently focused on answer gen…

cs.CL2022

Semantic Answer Type and Relation Prediction Task (SMART 2021)

Nandana Mihindukulasooriya, Mohnish Dubey, Alfio Gliozzo +5

Each year the International Semantic Web Conference organizes a set of Semantic Web Challenges to establish competitions that will advance state-of-the-art solutions in some proble…

cs.CL2021

Survey on English Entity Linking on Wikidata

Cedric Möller, Jens Lehmann, Ricardo Usbeck

Wikidata is a frequently updated, community-driven, and multilingual knowledge graph. Hence, Wikidata is an attractive basis for Entity Linking, which is evident by the recent incr…

cs.CL202012 cited

End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings

Rostislav Nedelchev, Debanjan Chaudhuri, Jens Lehmann +1

Entity linking - connecting entity mentions in a natural language utterance to knowledge graph (KG) entities is a crucial step for question answering over KGs. It is often based on…