Papers with OpenKGs
CaRe: Open Knowledge Graph Embeddings (D19-1)
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| Challenge: | Existing methods for generating Open Knowledge Graphs have been criticized for not achieving canonicalization of OpenKGs. |
| Approach: | They propose to use Open Information Extraction methods to extract triples from text . they propose to learn embeddings of NPs and RPs present in the graph . |
| Outcome: | The proposed methods improve OpenKG embeddings and bootstrap OpenKGs from text corpus. |
Alleviating Sparsity of Open Knowledge Graphs with Ternary Contrastive Learning (2022.findings-emnlp)
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| Challenge: | Existing approaches to learning KG triplets ignore ternary propagation patterns and ignore zero-shot, few-shot and synonymity problems. |
| Approach: | They propose a framework for contrastive learning based on ternary propagation patterns among head, relation and tail. |
| Outcome: | Experiments on benchmarks show that TernaryCL is superior to state-of-the-art models. |
OKGIT: Open Knowledge Graph Link Prediction with Implicit Types (2021.findings-acl)
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| Challenge: | Open Knowledge Graphs (OpenKGs) are sparse and not directly usable in an end task. |
| Approach: | They propose a method that bootstraps OpenKGs from a corpus using OpenIE tools. |
| Outcome: | The proposed method achieves state-of-the-art performance while producing type compatible NPs in the link prediction task. |