Complex Query Answering

The FB15k dataset contains knowledge base relation triples and textual mentions of Freebase entity pairs. It has a total of 592,213 triplets with 14,951 entities and 1,345 relationships. FB15K-237 is a variant of the original dataset where inverse relations are removed, since it was found that a large number of test triplets could be obtained by inverting triplets in the training set. Source: https://www.microsoft.com/en-us/download/details.aspx?id=52312 Image Source: http://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf

FB15k-237 is a link prediction dataset created from FB15k. While FB15k consists of 1,345 relations, 14,951 entities, and 592,213 triples, many triples are inverses that cause leakage from the training to testing and validation splits. FB15k-237 was created by Toutanova and Chen (2015) to ensure that the testing and evaluation datasets do not have inverse relation test leakage. In summary, FB15k-237 dataset contains 310,116 triples with 14,541 entities and 237 relation types.

NELL is a dataset built from the Web via an intelligent agent called Never-Ending Language Learner. This agent attempts to learn over time to read the web. NELL has accumulated over 50 million candidate beliefs by reading the web, and it is considering these at different levels of confidence. NELL has high confidence in 2,810,379 of these beliefs. Source: A Survey on Knowledge Graphs: Representation, Acquisition and Applications Image Source: http://rtw.ml.cmu.edu/rtw/

NELL-995 KG Completion Dataset

Genre annotations for movies The file genre2movies.csv contains genre-movie tuples based on Wikidata annotations (https://www.wikidata.org/). Data Each line in genre2movies.csv represents one genre-movie tuple. The first entry is the genre. The second entry of each line is the movie name. There are 83,670 genre-movie tuples. Joining with the Movielens 20M dataset The movies considered are from the Movielens 20M corpus: https://grouplens.org/datasets/movielens/20m/ The movie names in genre2movies.csv match the movie 'titles' in Movielens 20M. Compositions The directory "compositions" contains movies assigned to compositions of genres. The compositions are of the form: "genre A and genre B", "genre A and not genre B", "genre A and genre B and genre C", "genre A and genre B and not genre C". These assignments have been automatically generated from genre2movies.csv. We try to generate genre-compositions that are useful, e.g., for a "genre A and genre B" composition we ensure that genre B is not a subgenre of genre A, because an interesection of a superset with a subset is identical to the subset and does not form a new concept.