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Santos"},"license":"ISC","homepage":"https://github.com/andrefs/punuy-datasets#readme","keywords":["semantic","relations","semantic","similarity","evaluation","gold","standard","dataset"],"repository":{"type":"git","url":"git+ssh://git@github.com/andrefs/punuy-datasets.git"},"description":"[![Node.js CI](https://github.com/andrefs/punuy-datasets/actions/workflows/node.js.yml/badge.svg)](https://github.com/andrefs/punuy-datasets/actions/workflows/node.js.yml)","maintainers":[{"name":"andrefs","email":"andrefs@andrefs.com"}],"readme":"# punuy-datasets\n\n[![Node.js CI](https://github.com/andrefs/punuy-datasets/actions/workflows/node.js.yml/badge.svg)](https://github.com/andrefs/punuy-datasets/actions/workflows/node.js.yml)\n\nA collection of quantitative lexical semantic relations datasets, gathered from the academic literature, for the evaluation of semantic measures between concepts or entities. Currently focused on the English and Portuguese languages.\n\n## Datasets\n\n### English\n\n<!-- datasets-section-start-EN -->\n<!-- Automatically generated by ./src/scripts/update-readme.ts -->\n\n| # | ID | Name | Year  | Domain | Sim/Rel | References \n| --- | --- | --- | --- | --- | --- | --- |  \n| 1 | [rg65](./profiles/rg65) | Rubenstein and Goodenough (1965) | 1965 | general | sim | [paper 📑](https://dl.acm.org/doi/pdf/10.1145/365628.365657), [website 🌐](https://dl.acm.org/doi/pdf/10.1145/365628.365657) | \n| 2 | [mervis210](./profiles/mervis210) | Mervis 210 | 1975 | general | rel | [paper 📑](https://www.researchgate.net/profile/J-Hutchinson-3/publication/232570742_Nearest_Neighbor_Analysis_of_Psychological_Spaces/links/00b4953342b9cc0ed1000000/Nearest-Neighbor-Analysis-of-Psychological-Spaces.pdf?__cf_chl_tk=TYUjnEV._cacEm4VeeXyQfghi_rQs.xukfy5XPyVeuk-1736643598-1.0.1.1-G3dCZbzFacLlfPJ3mLAynHLHfBawHJAQSIYJJPCZTJc) | \n| 3 | [tversky42](./profiles/tversky42) | Tversky42 | 1979 | general | sim | [paper 📑](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=3840ba46475c2c8d39bb786d304584cb84ae0a10#page=92) | \n| 4 | [mc30](./profiles/mc30) | Miller and Charles (1991) | 1991 | general | sim | [paper 📑](https://sci-hub.se/https://doi.org/10.1080/01690969108406936) | \n| 5 | [medin34](./profiles/medin34) | Medin 34 | 1993 | general | sim | [paper 📑](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=d2c6fea244369a58e597e056eac0eac07c113bb9) | \n| 6 | [resnik28](./profiles/resnik28) | Miller and Charles Replication | 1999 | general | sim | [paper 📑](https://jair.org/index.php/jair/article/view/10236/24361), [website 🌐](https://jair.org/index.php/jair/article/view/10236/24361) | \n| 7 | [rd27](./profiles/rd27) | Resnik and Diab 2000 | 2000 | general | sim | [paper 📑](https://escholarship.org/content/qt9bw0t5sb/qt9bw0t5sb.pdf), [website 🌐](https://github.com/psresnik/verb_similarity_2000) | \n| 8 | [ws353](./profiles/ws353) | WordSimilarity-353 | 2002 | general | sim | [paper 📑](https://www.cs.tau.ac.il/~ruppin/p116-finkelstein.pdf), [website 🌐](https://www.cs.technion.ac.il/~gabr/resources/data/wordsim353/) | \n| 9 | [yp130](./profiles/yp130) | YP-130 | 2005 | general | sim | [paper 📑](http://david.wardpowers.info/Research/AI/papers/200601-GWC-VerbSimWN.pdf) | \n| 10 | [bg100k](./profiles/bg100k) | Princeton Evocation Data 0.4 | 2006 | general | evo | [paper 📑](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=bfeebec5eb0aacd24eb91c94687dfe47b461f5b4), [website 🌐](https://wordnet.cs.princeton.edu/downloads/evocation/release-0.4) | \n| 11 | [mesh2](./profiles/mesh2) | MeSH2 | 2006 | biomedical | sim | [paper 📑](https://users.uop.gr/~praftop/papers/pdf/wms06-PVHR.pdf), [website 🌐](https://www.intelligence.tuc.gr/similarity/datasets.php) | \n| 12 | [zie55](./profiles/zie55) | Ziegler et al. (2006) | 2006 | general | rel | [paper 📑](https://web.archive.org/web/20070824183036id_/http://www.informatik.uni-freiburg.de/~ksimon/papers/CIKM-06-Proximity.pdf) | \n| 13 | [mayoSRS](./profiles/mayoSRS) | MayoSRS | 2007 | biomedical | rel | [paper 📑](https://www.sciencedirect.com/science/article/pii/S1532046406000645?via%3Dihub), [website 🌐](https://conservancy.umn.edu/handle/11299/196265) | \n| 14 | [miniMSRS](./profiles/miniMSRS) | MiniMayoSRS | 2007 | biomedical | rel | [paper 📑](https://www.sciencedirect.com/science/article/pii/S1532046406000645?via%3Dihub), [website 🌐](https://conservancy.umn.edu/handle/11299/196265) | \n| 15 | [gm30](./profiles/gm30) | Gracia and Mena (2008) | 2008 | general | rel | [paper 📑](https://oa.upm.es/6549/1/Web-based_Measure.pdf) | \n| 16 | [ps65](./profiles/ps65) | Pirro and Seco (2008) | 2008 | general | sim | [paper 📑](https://dl.acm.org/doi/abs/10.1007/978-3-540-88873-4_25) | \n| 17 | [ws353split](./profiles/ws353split) | WordSim-353 Similarity and Relatedness Gold Standard | 2009 | general | rel/sim | [paper 📑](https://aclanthology.org/N09-1003.pdf), [website 🌐](http://alfonseca.org/eng/research/wordsim353.html) | \n| 18 | [umnsrs](./profiles/umnsrs) | UMNSRS | 2010 | biomedical | rel/sim | [paper 📑](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041430/pdf/amia-2010_sympproc_0572.pdf), [website 🌐](https://conservancy.umn.edu/handle/11299/196265) | \n| 19 | [mt287](./profiles/mt287) | MT287 | 2011 | general | rel | [paper 📑](http://www.kiraradinsky.com/files/Radinsky-TemporalSemantics.pdf), [website 🌐](http://www.kiraradinsky.com/Datasets.html) | \n| 20 | [atlasify240](./profiles/atlasify240) | Atlasify240 | 2012 | general | rel | [paper 📑](https://www.brenthecht.com/papers/bhecht_sigir2012_ExpSpatialization_SRplusE.pdf), [website 🌐](https://users.cs.northwestern.edu/~ddowney/data_code.html) | \n| 21 | [kore420](./profiles/kore420) | KORE: Related Entities Dataset | 2012 | general | rel | [paper 📑](https://dl.acm.org/doi/pdf/10.1145/2396761.2396832), [website 🌐](https://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/ambiverse-nlu/aida/downloads) | \n| 22 | [mturk771](./profiles/mturk771) | MTurk771 | 2012 | general | rel | [paper 📑](https://www-ai.cs.tu-dortmund.de/LEHRE/FACHPROJEKT/WS1213/WordCorrelations.pdf), [website 🌐](http://www2.mta.ac.il/~gideon/datasets/mturk_771.html) | \n| 23 | [reword26](./profiles/reword26) | REWOrD | 2012 | general | rel | [paper 📑](https://cdn.aaai.org/ojs/8107/8107-13-11634-1-2-20201228.pdf), [website 🌐](https://relwod.wordpress.com/datasets/) | \n| 24 | [scws2003](./profiles/scws2003) | SCWS | 2012 | general | sim | [paper 📑](https://aclanthology.org/P12-1092.pdf), [website 🌐](https://ai.stanford.edu/~ehhuang/) | \n| 25 | [ma28](./profiles/ma28) | Martinez & Aldana | 2013 | general | sim | [paper 📑](https://hal.science/hal-01628399/file/article.pdf), [website 🌐](https://hal.science/hal-01628399/file/article.pdf) | \n| 26 | [rel122](./profiles/rel122) | Rel-122 | 2013 | general | rel | [paper 📑](https://aclanthology.org/P13-2154.pdf), [website 🌐](https://www.cs.ucf.edu/~seansz/rel-122/) | \n| 27 | [srw2034](./profiles/srw2034) | Stanford Rare Word (RW) Similarity Dataset | 2013 | general | sim | [paper 📑](https://nlp.stanford.edu/~lmthang/data/papers/conll13_morpho.pdf), [website 🌐](https://nlp.stanford.edu/~lmthang/morphoNLM/) | \n| 28 | [wp300](./profiles/wp300) | WP300 | 2013 | general | sim | [paper 📑](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/CIKM841-Li.pdf), [website 🌐](http://adapt.seiee.sjtu.edu.cn/similarity/) | \n| 29 | [baker143](./profiles/baker143) | Baker 143 | 2014 | general | sim | [paper 📑](https://aclanthology.org/D14-1034.pdf), [website 🌐](https://github.com/sb895/verb-similarity-dataset) | \n| 30 | [geresid50](./profiles/geresid50) | GeReSiD | 2014 | geographical | rel/sim | [paper 📑](https://arxiv.org/pdf/1402.3371), [website 🌐](https://github.com/ucd-spatial/Datasets/tree/master/geresid-geo_relatedness_similarity_dataset) | \n| 31 | [men3000](./profiles/men3000) | MEN | 2014 | general | rel | [paper 📑](https://core.ac.uk/download/pdf/35317232.pdf), [website 🌐](https://staff.fnwi.uva.nl/e.bruni/MEN) | \n| 32 | [sl7576](./profiles/sl7576) | SL7576 | 2014 | general | sim | [paper 📑](https://aclanthology.org/P14-1068.pdf), [website 🌐](https://sites.google.com/view/carinasilberer) | \n| 33 | [lm659](./profiles/lm659) | Landrigan & Mirman (2015) | 2015 | general | rel/sim | [paper 📑](https://openpsychologydata.metajnl.com/articles/10.5334/jopd.24), [website 🌐](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/FKTQ4C) | \n| 34 | [simlex999](./profiles/simlex999) | SimLex-999 | 2015 | general | sim | [paper 📑](https://aclanthology.org/J15-4004.pdf), [website 🌐](https://fh295.github.io/simlex.html) | \n| 35 | [tr9856](./profiles/tr9856) | TR9856 | 2015 | general | rel | [paper 📑](https://aclanthology.org/P15-2069.pdf), [website 🌐](https://developer.ibm.com/exchanges/data/all/multi-word-term-relatedness-benchmark/) | \n| 36 | [simverb3500](./profiles/simverb3500) | SimVerb-3500 | 2016 | general | sim | [paper 📑](https://aclanthology.org/D16-1235.pdf), [website 🌐](https://www.repository.cam.ac.uk/items/8a568201-0fa4-4e54-81b1-f920102492ea) | \n| 37 | [umnsrsMod](./profiles/umnsrsMod) | UMNSRS (modified) | 2016 | biomedical | rel/sim | [paper 📑](https://academic.oup.com/bioinformatics/article/32/23/3635/2525643), [website 🌐](https://conservancy.umn.edu/handle/11299/196265) | \n| 38 | [semeval17](./profiles/semeval17) | SemEval-2017 Task 2.1 | 2017 | general | sim | [paper 📑](https://aclanthology.org/S17-2002.pdf), [website 🌐](https://alt.qcri.org/semeval2017/task2/) | \n| 39 | [ali27](./profiles/ali27) | Ali et al. 2018 | 2018 | general | sim | [paper 📑](https://www.researchgate.net/profile/Ashraf-Ali-31/publication/329755771_SEMANTIC_SIMILARITY_MEASURES_BETWEEN_WORDS_A_BRIEF_SURVEY/links/5c192917458515a4c7e7831e/SEMANTIC-SIMILARITY-MEASURES-BETWEEN-WORDS-A-BRIEF-SURVEY.pdf) | \n| 40 | [card660](./profiles/card660) | Card-660 | 2018 | general | sim | [paper 📑](https://pilehvar.github.io/card-660/Card-660.pdf), [website 🌐](https://pilehvar.github.io/card-660/) | \n| 41 | [gtrd](./profiles/gtrd) | GTRD | 2018 | geographical | rel | [paper 📑](https://pdfs.semanticscholar.org/f8f1/b82386147b6a9142b2cff2dc662a3e614d80.pdf), [website 🌐](https://github.com/czgbjy/GTRD) | \n| 42 | [word19k](./profiles/word19k) | Wikipedia Oriented Relatedness Dataset | 2018 | general | rel | [paper 📑](https://aclanthology.org/L18-1408.pdf), [website 🌐](https://developer.ibm.com/exchanges/data/all/wikipedia-oriented-relatedness/) | \n| 43 | [multisimlex](./profiles/multisimlex) | Multi-SimLex | 2020 | general | sim | [paper 📑](https://multisimlex.com/Multi-SimLex-Paper.pdf), [website 🌐](https://multisimlex.com/) | \n| 44 | [emocon](./profiles/emocon) | Emotion concepts 2022 | 2022 | emotional | sim | [paper 📑](https://escholarship.org/content/qt8vj3d366/qt8vj3d366.pdf), [website 🌐](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6DPPKH) | \n| 45 | [sstars13](./profiles/sstars13) | Shooting-Stars | 2023 | general | rel | [paper 📑](https://drive.google.com/file/d/1PNlPMH2lQx3BJI8kEAQjVeLoiezeY1x8/view), [website 🌐](https://github.com/andrefs/grettir-datasets/blob/main/stars-2021115.txt) | \n\n<!-- datasets-section-end-EN -->\n\n### Portuguese\n\n<!-- datasets-section-start-PT -->\n<!-- Automatically generated by ./src/scripts/update-readme.ts -->\n\n| # | ID | Name | Year  | Domain | Sim/Rel | References \n| --- | --- | --- | --- | --- | --- | --- |  \n| 1 | [pt65](./profiles/pt65) | PT65 | 2014 | general | rel | [paper 📑](https://hal.science/hal-02089290/file/leitzkegranada_22675.pdf), [website 🌐](http://www.inf.pucrs.br/linatural/wikimodels/similarity.html) | \n| 2 | [lxrw2034](./profiles/lxrw2034) | LX-Rare Word Similarity Dataset | 2017 | general | sim | [paper 📑](https://www.grupocole.org/cole/library/ps/QueCarRodGarSilCorRenPerCamBra2017a.pdf), [website 🌐](https://portulanclarin.net/repository/browse/lx-rare-word-similarity-dataset/f8dd0332e6d911e6a2aa782bcb074135a226cf379cf746a8976dd3420f5a2813/) | \n| 3 | [lxsimlex999](./profiles/lxsimlex999) | LX-SimLex-999 | 2017 | general | sim | [paper 📑](https://www.grupocole.org/cole/library/ps/QueCarRodGarSilCorRenPerCamBra2017a.pdf), [website 🌐](https://portulanclarin.net/repository/browse/lx-simlex-999/4ab1ea58e6d311e6a2aa782bcb0741351e920e18429e4d3e9d229a58030812fe/) | \n| 4 | [lxws353](./profiles/lxws353) | LX-WordSim-353 | 2017 | general | rel | [paper 📑](https://www.grupocole.org/cole/library/ps/QueCarRodGarSilCorRenPerCamBra2017a.pdf), [website 🌐](https://portulanclarin.net/repository/browse/lx-wordsim-353/c4e08b72e6dd11e6a2aa782bcb074135a5ac38ba70a14fb3adbd5782b21dacb0/) | \n| 5 | [pap900](./profiles/pap900) | PAP900 | 2024 | emotional | rel/sim | [website 🌐](https://github.com/andrefs/PAP900) | \n\n<!-- datasets-section-end-PT -->\n\n## Use with Node.js\n\nIf you want to programatically use the datasets' data and metadata, install the Node.js wrapper code:\n\n```\nnpm install\n```\n\nThen you can access the datasets like this:\n\n```javascript\nimport { mc30, rg65 } from \"punuy-datasets\";\n\nfor (const part of mc30.partitions) {\n  console.log(part.id, part.data.length); // print partition id and size\n}\n```\n\n## Other uses\n\nIf you want to use another language or just want to access the data files directly, each dataset has its own folder inside `profiles/`.\n\nEach dataset has a `dataset.json` file with its metadata and information about its partitions. Then, for each partition with id `p_id`, there is a `p_id.part.json` file containing the pairs and their ratings.\n\n## Non-open datasets\n\nSome datasets have licenses which explicitly prevent them from being redistributed.\nCurrently this includes the following datasets:\n\n- lxrw2034\n- lxsimlex999\n- lxws353\n\nIn this cases you have to download the datasets files manually, but after saving them in the right folders they can be automatically imported.\n\nWe can guide you through this process. Just run\n\n```bash\ncd node_modules/punuy-datasets # if you're using punuy-datasets as a dependency\nnpm run download-non-open\n```\n\nand follow the instructions provided on the console.\n\n## Adding a new dataset\n\nIf you can create the dataset profile yourself, [PRs](https://github.com/andrefs/punuy-datasets/pulls) are welcome!\nYou can find the dataset schema (in Typescript) [here](./src/lib/types.ts).\n\nOr you can open an [issue](https://github.com/andrefs/punuy-datasets/issues). Please include:\n\n1. a link to the dataset homepage (if it exists),\n1. a link to download the dataset, and\n1. a link to the paper describing it.\n\nI'll get to it as soon as I find some free time ;)\n\n## Types and schema\n\nTypeScript definitions can be found at [src/lib/types.ts](src/lib/types.ts).\n\nAutomatically generated JSON schema definitions can be found at [dataset-schema.json](dataset-schema.json) and [partition-data-schema.json](partition-data-schema.json).\n\nAutomatically generated documentation can be found at [docs/](docs/).\n\n## Datasets copyright and licenses\n\nDid you find a problem with the licensing of a dataset?\nWe did our best to find and include the licenses to all the datasets and to respect copyrights, but we might have missed something!\n\nPlease [open an issue](https://github.com/andrefs/punuy-datasets/issues) and we'll fix it ASAP.\n\n## See also\n\nFor cross-lingual datasets and datasets in other languages please check the following links:\n\n- [Mohamed Ali Hadj Taieb's repository](https://github.com/MohamedAliHadjTaieb/Semantic-measure-assessment-review-study)\n\n## Bugs and stuff\n\nOpen a [GitHub issue](https://github.com/andrefs/punuy-datasets/issues) or, preferably, send me a [pull request](https://github.com/andrefs/punuy-datasets/pulls).\n\n## License\n\nThe MIT License (MIT)\n\nCopyright (c) 2025 André Santos <andrefs@andrefs.com>\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \"Software\"), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of\nthe Software, and to permit persons to whom the Software is furnished to do so,\nsubject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR\nCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER\nIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN\nCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n","readmeFilename":"README.md"}