Comments (10)
The paper doesn't introduce any new dataset.
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Shall I merge the pull request #108 ?
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No, a new pull request per issue is recommended
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relevant pull request: #167
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@DavidBlavid Are these numbers correct? I cannot find them in this pull request.
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Because we do not differentiate between before/after, first/last and time join in cron_questions.md, i calculated the averages for the numbers. So for AE-TQ (0.542 + 0.762 + 0.737)/3 = 0.680 for Hits@1 and (0.701 + 0.793 + 0.767)/3 = 0.754 for Hits@3.
Please let me know if this is correct or if i should change it
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Should we add a footnote for it? @xixi019
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Because we do not differentiate between before/after, first/last and time join in cron_questions.md, i calculated the averages for the numbers. So for AE-TQ (0.542 + 0.762 + 0.737)/3 = 0.680 for Hits@1 and (0.701 + 0.793 + 0.767)/3 = 0.754 for Hits@3.
Please let me know if this is correct or if i should change it
I replied in this comment: #167 (comment)
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I have created a new pull request based on the reviews: #174
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Related Issues (20)
- Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs
- Self-Improvement Programming for Temporal Knowledge Graph Question Answering
- M 3 TQA: Multi-View, Multi-Hop and Multi-Stage Reasoning for Temporal Question Answering
- A Knowledge-Injected Curriculum Pretraining Framework for Question Answering
- CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge
- Lingua Franca – Entity-Aware Machine Translation Approach for Question Answering over Knowledge Graphs
- MarkQA: A large scale KBQA dataset with numerical reasoning
- Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
- Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering
- From Parse-Execute to Parse-Execute-Refine: Improving Semantic Parser for Complex Question Answering over Knowledge Base
- add "Language Models as SPARQL Query Filtering for Improving the Quality of Multilingual Question Answering over Knowledge Graphs"
- add "DARA: Decomposition-Alignment-Reasoning Autonomous Language Agent for Question Answering over Knowledge Graphs"
- systems.md vs. systems_updated.md
- Dynamic Few-Shot Learning for Knowledge Graph Question Answering
- Generating SPARQL from Natural Language Using Chain-of-Thoughts Prompting
- Knowledge Base Question Answering based on Machine Reading Comprehension
- Code-Style In-Context Learning for Knowledge-Based Question Answering
- QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback-based Self-Correction
- MST5 — A Transformers-Based Approach to Multilingual Question Answering over Knowledge Graphs
- Incorporating multi-perspective information into reinforcement learning to address multi-hop knowledge graph question answering
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