Papers with KG triples
Improving Knowledge Graph Embedding Using Simple Constraints (P18-1)
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| Challenge: | Recent efforts focused on designing more complicated models or incorporating extra information beyond triples. |
| Approach: | They propose to use non-negativity constraints on entity representations and approximate entailment constraints on relation representations to improve KG embedding. |
| Outcome: | The proposed model outperforms baseline models on WordNet, Freebase, and DBpedia. |
Bi-Directional Multi-Granularity Generation Framework for Knowledge Graph-to-Text with Large Language Model (2024.acl-short)
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| Challenge: | Existing methods generate whole text based on all KG triples at once and may incorporate incorrect KG Triples for each sentence. |
| Approach: | They propose a bi-directional multi-granularity generation framework that generates graph-level sentences based on KG triples instead of the whole text at a time. |
| Outcome: | The proposed framework achieves state-of-the-art in benchmark dataset WebNLG and further analysis shows the efficiency of different modules. |
Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering (2024.emnlp-main)
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| Challenge: | Existing Knowledge Graph Question Answering (KGQA) methods focus on answering factual questions, leaving questions involving commonsense reasoning unaddressed. |
| Approach: | They propose a commonsense KGQA methodology that axiomatically surfaces commonsensical knowledge of Large Language Models and grounding every factual reasoning step on KG triples. |
| Outcome: | The proposed method outperforms existing methods and reduces instances of hallucination and reasoning errors. |