ConceptNet Numberbatch is a set of semantic vectors (also known as word embeddings) than can be used directly as a representation of word meanings or as a starting point for further machine learning. ConceptNet Numberbatch is part of the ConceptNet open data project. ConceptNet is a knowledge graph that provides lots of ways to compute with word meanings, one of which is word embeddings, while ConceptNet Numberbatch is a snapshot of just the word embeddings. These embeddings benefit from the fact that they have semi-structured, common sense knowledge from ConceptNet, giving them a way to learn about words that isn’t just observing them in context. Numberbatch is built using an ensemble that combines data from ConceptNet, word2vec, GloVe, and OpenSubtitles 2016, using a variation on retrofitting. It is described in the paper ConceptNet 5.5: An Open Multilingual Graph of General Knowledge, presented at AAAI 2017.
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- Claudia Schon, Sophie Siebert, Frieder Stolzenburg: Using ConceptNet to Teach Common Sense to an Automated Theorem Prover (2019) arXiv