Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion (2022.coling-1)
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| Challenge: | Knowledge Graph Completion (KGC) has been extended to multiple knowledge graph (KG) structures, initiating new research directions, e.g. static KGC, temporal KGC and few-shot KGC. |
| Approach: | They propose a generative framework that could tackle different verbalizable graph structures by unifying the representation of KG facts into "flat" text. |
| Outcome: | The proposed framework outperforms many competitive baselines and sets new state-of-the-art performance on five benchmarks. |
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| Challenge: | Existing embedding-based methods rely on triples in the KG, which is vulnerable to specious relation patterns and long-tail entities. |
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| Challenge: | Knowledge graph completion (KGC) methods are computationally intensive and impractical for large-scale KGs. |
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| Challenge: | Existing knowledge graph completion methods perform simple linear update on relation representation, and only local neighborhood information is aggregated, making it difficult to capture logic semantic between relations and global topological context information. |
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| Challenge: | Text-based knowledge graph completion methods neglect knowledge contexts in inferring process. |
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| Challenge: | Existing approaches to Knowledge Graph Completion use textual descriptions of the KG entities and relations to perform the task. |
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KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion (2023.findings-emnlp)
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| Challenge: | Existing knowledge graph completion methods struggle with long-tail entities due to limited structural information and imbalanced distributions of entities. |
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| Challenge: | Existing knowledge graph completion methods ignore inconsistent representation spaces between natural language and graph structures, leading to duplicate works and time-consuming processes. |
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| Challenge: | Knowledge graphs (KGs) are incomplete because of the large number of benchmark datasets that are not representative of real KGs. |
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