GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering.
Debayan BanerjeePranav Ajit NairRicardo UsbeckChris BiemannPublished in: CoRR (2023)
Keyphrases
- question answering
- graph embedding
- question classification
- information extraction
- natural language processing
- qa clef
- passage retrieval
- qa systems
- natural language
- discriminant analysis
- cross language
- open domain question answering
- low dimensional
- information retrieval
- dimensionality reduction
- expert systems
- graph structure
- natural language questions
- prior knowledge
- knowledge base
- semi supervised
- answer validation
- knowledge representation
- answer extraction
- question answering systems
- structured data
- syntactic information
- candidate answers
- question answer pairs
- text mining
- machine learning
- similarity measure
- pattern recognition
- high dimensional
- relational databases
- data representation
- test set
- image classification
- data mining techniques