8 datasets found

Knowledge-based visual question answering (KVQA) has been extensively studied to answer visual questions with external knowledge, e.g., knowledge graphs (KGs).

The dataset consists of 119 clusters, with a total of 584 questions, which include 4 different linguistic forms per query, so we have approximately 146 semantically different...

Knowledge graphs are composed of different elements: entity nodes, relation edges, and literal nodes. Each literal node contains an entity’s attribute value (e.g. the height of...

The dataset used in the paper is Wikidata, which contains a large number of entities and their corresponding semantic types.

DBpedia is a public knowledge graph which is derived from structured information in Wikipedia, mainly infoboxes.

Knowledge graphs (KGs) are collections of facts. Some well-known knowledge graphs include Freebase (Bollacker et al., 2008), Word-Net (Miller, 1995), YAGO (Suchanek et al.,...

Knowledge graphs store a wealth of knowledge from the real world into structured graphs, which consist of collections of triplets, and each triplet (h, r, t) represents that...

The dataset used in this paper is a reinforcement learning dataset, specifically the SimpleQuestion dataset, which contains questions answerable using Wikidata as the knowledge...