mlsanityData to 14 Oct 2026

GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering

arXiv 2303.13284 ↗First posted 23 Mar 2023cs.CL cs.DB cs.IRcited by 6

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Abstract (arXiv)

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 takes a question in natural language as input and produces a simpler form of the intended SPARQL query. In the simpler form, the model does not directly produce entity and relation IDs. Instead, it produces corresponding entity and relation labels. The labels are grounded to KG entity and relation IDs in a subsequent step. To further improve the results, we instruct the model to produce a truncated version of the KG embedding for each entity. The truncated KG embedding enables a finer search for disambiguation purposes. We find that T5 is able to learn the truncated KG embeddings without any change of loss function, improving KGQA performance. As a result, we report strong results for LC-QuAD 2.0 and SimpleQuestions-Wikidata datasets on end-to-end KGQA over Wikidata.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 31 of its 47 references that are in the map. First posted on arXiv 23 Mar 2023.

Builds on

31 of 47 references.

References · 31

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2017Graph Attention Networkscited by 8,923
  5. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,694
  6. 2019KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representationcited by 356
  7. 2019K-BERT: Enabling Language Representation with Knowledge Graphcited by 304
  8. 2019PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Textcited by 184
  9. 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 168
  10. 2015Large-scale Simple Question Answering with Memory Networkscited by 127
  11. 2019PyTorch-BigGraph: A Large-scale Graph Embedding Systemcited by 119
  12. 2020CoLAKE: Contextualized Language and Knowledge Embeddingcited by 86
19 more
  1. 2020Message Passing for Hyper-Relational Knowledge Graphscited by 79
  2. 2021A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutionscited by 78
  3. 2020JAKET: Joint Pre-training of Knowledge Graph and Language Understandingcited by 73
  4. 2021Complex Temporal Question Answering on Knowledge Graphscited by 69
  5. 2018Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graphcited by 67
  6. 2020UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answeringcited by 61
  7. 2019Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansioncited by 42
  8. 2022Modern Baselines for SPARQL Semantic Parsingcited by 34
  9. 2019Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Basecited by 33
  10. 2019Message Passing for Complex Question Answering over Knowledge Graphscited by 24
  11. 2021Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networkscited by 24
  12. 2021UNIQORN: Unified Question Answering over RDF Knowledge Graphs and Natural Language Textcited by 17
  13. 2021A Two-Stage Approach towards Generalization in Knowledge Base Question Answeringcited by 15
  14. 2018Towards a Question Answering System over the Semantic Webcited by 14
  15. 2021KI-BERT: Infusing Knowledge Context for Better Language and Domain Understandingcited by 11
  16. 2021Context Transformer with Stacked Pointer Networks for Conversational Question Answering over Knowledge Graphscited by 10
  17. 2021SYGMA: System for Generalizable Modular Question Answering OverKnowledge Basescited by 8
  18. 2022MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answeringcited by 4
  19. 2021Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linkingcited by 3

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 1; 2025: 2.

6 papers.

  1. 2023Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graphcited by 238
  2. 2023Leveraging LLMs in Scholarly Knowledge Graph Question Answeringcited by 13
  3. 2024SPARKLE: Enhancing SPARQL Generation with Direct KG Integration in Decodingcited by 5
  4. 2025Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learningcited by 5
  5. 2025Aligning Knowledge Graphs and Language Models for Factual Accuracycited by 4
  6. 2023UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphscited by 0