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Found 4 papers, 3 papers with code
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak Supervision
The majority of knowledge graph embedding techniques treat entities and predicates as separate embedding matrices, using aggregation functions to build a representation of the input triple.
Clustering and Network Analysis for the Embedding Spaces of Sentences and Sub-Sentences
Sentence embedding methods offer a powerful approach for working with short textual constructs or sequences of words.
A Survey of Embedding Space Alignment Methods for Language and Knowledge Graphs
Neural embedding approaches have become a staple in the fields of computer vision, natural language processing, and more recently, graph analytics.
A Comparative Study on Structural and Semantic Properties of Sentence Embeddings
Although a number of techniques have been proposed in the literature for embedding both sentences and knowledge graphs, little is known about the structural and semantic properties of these embedding spaces in terms of relation extraction.
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