Knowledge Graph Representation with Jointly Structural and Textual Encoding · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/1611.08661/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTKnowledge Graph Representation with Jointly Structural and Textual Encoding — mentioned by mulletboyhttps://news.ycombinator.com/item?id=19581179urn:hackerpapers:mention:1611.08661:19581179Fri, 05 Apr 2019 10:18:17 GMT<p>&gt; what are possible inputs to ampligraph? Any knowledge graph will do (i.e. directed, labeled multigraph, with or without schema). We have APIs to read graphs serialised as CSV files or RDF (any serialisation will do): http://docs.ampligraph.org/en/1.0.1/ampligraph.datasets.html... &gt; the main use-case is plugging in an existing knowledge graph, and it filling in the gaps Correct. That is known as Link Prediction. There are other machine learning tasks you can do, though: for example you can generate embeddings and then cluster them. Or you can use embeddings to see if distinct entities are…</p><p><a href="https://hackerpaper.kaipfister.de/p/1611.08661/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CL