  One of the big challenges in Linked Data consumption is to create visual and
natural language interfaces to the data usable for non-technical users. Ontodia
provides support for diagrammatic data exploration, showcased in this
publication in combination with the Wikidata dataset. We present improvements
to the natural language interface regarding exploring and querying Linked Data
entities. The method uses models of distributional semantics to find and rank
entity properties related to user input in Ontodia. Various word embedding
types and model settings are evaluated, and the results show that user
experience in visual data exploration benefits from the proposed approach.
