{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/conceptnet-55-an-open-multilingual-graph-of","title":"ConceptNet 5.5: An Open Multilingual Graph of General Knowledge","arxiv_id":"1612.03975","date":"2016-12-12","proceeding":null,"authors":["Robyn Speer","Joshua Chin","Catherine Havasi"],"abstract":"Machine learning about language can be improved by supplying it with specific\nknowledge and sources of external information. We present here a new version of\nthe linked open data resource ConceptNet that is particularly well suited to be\nused with modern NLP techniques such as word embeddings.\n  ConceptNet is a knowledge graph that connects words and phrases of natural\nlanguage with labeled edges. Its knowledge is collected from many sources that\ninclude expert-created resources, crowd-sourcing, and games with a purpose. It\nis designed to represent the general knowledge involved in understanding\nlanguage, improving natural language applications by allowing the application\nto better understand the meanings behind the words people use.\n  When ConceptNet is combined with word embeddings acquired from distributional\nsemantics (such as word2vec), it provides applications with understanding that\nthey would not acquire from distributional semantics alone, nor from narrower\nresources such as WordNet or DBPedia. We demonstrate this with state-of-the-art\nresults on intrinsic evaluations of word relatedness that translate into\nimprovements on applications of word vectors, including solving SAT-style\nanalogies.","url_abs":"http://arxiv.org/abs/1612.03975v2","url_pdf":"http://arxiv.org/pdf/1612.03975v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/commonsense/conceptnet-numberbatch","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/LuminosoInsight/conceptnet-vector-ensemble","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/NathanDuran/Sentence-Encoding-for-DA-Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"GPL-3.0"}},{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/avi-jit/SWOW-eval","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/karanthakkar97/Text-summarization-with-Seq2Seq","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"conceptnet-55-an-open-multilingual-graph-of","repo_url":"https://github.com/shayanray/ApplyingCommonSense","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"general-knowledge","task_name":"General Knowledge"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[{"slug":"conceptnet","name":"ConceptNet","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1612.03975","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1612.03975"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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