37 datasets found

The dataset used for contextualized link prediction in knowledge graphs

The proposed method for Object-agnostic State Classification (OaSC) combines structured knowledge on object states with visual information that relates the appearance of certain...

Knowledge graphs (KGs) such as Freebase (Bollacker et al. 2008), DBpedia (Auer et al. 2007), and YAGO (Mahdisoltani, Biega, and Suchanek 2014) play a critical role in various...

The dataset used in the paper is SNLI, SciTail, and BreakingNLI.

The EnhancedKGP dataset is an enhanced version of the BaseKGP dataset, which is a knowledge graph dataset used for multi-hop path reasoning tasks. The dataset is used to...

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

Knowledge graphs store semantic information in the form of entities and relationships that is easily machine-processable — a property that is considered as an important...

Knowledge graphs store semantic information in the form of entities and relationships that is easily machine-processable — a property that is considered as an important...

WikiKG90M is a Knowledge Graph extracted from the entire Wikidata knowledge base.

A benchmark for complex temporal question answering on knowledge graphs.

A benchmark for temporal question answering with knowledge graph.

The dataset used in the paper is a knowledge graph dataset, specifically the Freebase dataset, which is a large-scale knowledge graph. The dataset is used for multi-hop path...

The OK-VQA dataset is a visual question answering benchmark requiring external knowledge.

A dataset for interactive recommender systems, used to evaluate the proposed Tree-structured Policy Gradient Recommendation (TPGR) framework.

FVQA is a fact-based visual question answering dataset, containing 2190 images and 5826 (question, answer) pairs, with supporting facts selected from knowledge bases.

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 for training and testing the Neural Variational Set Expansion (NVSE) model.

NELL is a large-scale, open knowledge graph that contains a vast amount of structured data.

The DBP15KZH-EN, DBP15KJA-EN, and DBP15KFR-EN datasets are used for cross-lingual entity alignment. The datasets contain entities, relations, and attributes, and are used to...

The FB15K-DB15K and FB15K-YAGO15K datasets are used for multi-modal entity alignment. The datasets contain entities, relations, triples, and images, and are used to evaluate the...