GETT-QA: Graph Embedding Based T2T Transformer for Knowledge Graph Question Answering.
Debayan BanerjeePranav Ajit NairRicardo UsbeckChris BiemannPublished in: ESWC (2023)
Keyphrases
- question answering
- graph embedding
- information extraction
- question classification
- natural language processing
- qa systems
- information retrieval
- discriminant analysis
- natural language
- passage retrieval
- cross language
- low dimensional
- semi supervised
- data representation
- answer extraction
- natural language questions
- qa clef
- artificial intelligence
- open domain question answering
- syntactic information
- question answering systems
- graph structure
- candidate answers
- text mining
- prior knowledge
- knowledge representation
- answer validation
- knowledge base