14 datasets found

AriGraph is a novel knowledge graph world model designed for LLM agents. It integrates semantic and episodic memories within a memory graph framework.

ALCUNA is a benchmark for evaluating the ability of large language models (LLMs) to handle new knowledge.

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...

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

MathGloss is a project to create a knowledge graph (KG) for undergraduate mathematics from text, automatically, using modern natural language processing (NLP) tools and...

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.

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.,...

The FB15K-YAGO15K dataset is a benchmark for multi-modal entity alignment.

The FB15K-DB15K dataset is an entity alignment dataset of FB15K and DB15K MMKGs.

ConceptNet is an open, multilingual knowledge graph that focuses on general knowledge that relates the meanings of words and phrases.

The dataset used in the paper is Music, Book, Amazon, and Yelp. The dataset contains user-item interactions and knowledge graph information.

The CPQA dataset consists of a cloud product knowledge graph (CPKG) and QA pairs. The dataset is used for domain-specific question answering (QA) tasks.

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