Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Multilinguality:
monolingual
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
License:
File size: 13,864 Bytes
e73b0cb caaf716 e73b0cb caaf716 ef6bfe2 e73b0cb ef6bfe2 e73b0cb 7c359d7 c7ec595 075e1c6 394eea5 075e1c6 394eea5 075e1c6 394eea5 075e1c6 394eea5 075e1c6 394eea5 075e1c6 394eea5 075e1c6 e73b0cb 7c359d7 e73b0cb 7c359d7 e73b0cb 3902476 e73b0cb 0455262 e73b0cb 0455262 3902476 394eea5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 |
---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- found
language:
- de
- en
- es
- fr
- it
- ja
- nl
- pt
- ru
- zh
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 10M<n<100M
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
paperswithcode_id: conceptnet
pretty_name: Conceptnet5
config_names:
- conceptnet5
- omcs_sentences_free
- omcs_sentences_more
dataset_info:
- config_name: conceptnet5
features:
- name: sentence
dtype: string
- name: full_rel
dtype: string
- name: rel
dtype: string
- name: arg1
dtype: string
- name: arg2
dtype: string
- name: lang
dtype: string
- name: extra_info
dtype: string
- name: weight
dtype: float32
splits:
- name: train
num_bytes: 11493772756
num_examples: 34074917
download_size: 1280623369
dataset_size: 11493772756
- config_name: omcs_sentences_free
features:
- name: sentence
dtype: string
- name: raw_data
dtype: string
- name: lang
dtype: string
splits:
- name: train
num_bytes: 174810230
num_examples: 898160
download_size: 72941617
dataset_size: 174810230
- config_name: omcs_sentences_more
features:
- name: sentence
dtype: string
- name: raw_data
dtype: string
- name: lang
dtype: string
splits:
- name: train
num_bytes: 341421867
num_examples: 2001735
download_size: 129630544
dataset_size: 341421867
configs:
- config_name: conceptnet5
data_files:
- split: train
path: conceptnet5/train-*
default: true
- config_name: omcs_sentences_free
data_files:
- split: train
path: omcs_sentences_free/train-*
- config_name: omcs_sentences_more
data_files:
- split: train
path: omcs_sentences_more/train-*
---
# Dataset Card for Conceptnet5
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://github.com/commonsense/conceptnet5/wiki
- **Repository:** https://github.com/commonsense/conceptnet5/wiki
- **Paper:** https://arxiv.org/abs/1612.03975
### Dataset Summary
ConceptNet is a multilingual knowledge base, representing words and
phrases that people use and the common-sense relationships between
them. The knowledge in ConceptNet is collected from a variety of
resources, including crowd-sourced resources (such as Wiktionary and
Open Mind Common Sense), games with a purpose (such as Verbosity and
nadya.jp), and expert-created resources (such as WordNet and JMDict).
You can browse what ConceptNet knows at http://conceptnet.io.
This dataset is designed to provide training data
for common sense relationships pulls together from various sources.
The dataset is multi-lingual. See langauge codes and language info
here: https://github.com/commonsense/conceptnet5/wiki/Languages
This dataset provides an interface for the conceptnet5 csv file, and
some (but not all) of the raw text data used to build conceptnet5:
omcsnet_sentences_free.txt, and omcsnet_sentences_more.txt.
One use of this dataset would be to learn to extract the conceptnet
relationship from the omcsnet sentences.
Conceptnet5 has 34,074,917 relationships. Of those relationships,
there are 2,176,099 surface text sentences related to those 2M
entries.
omcsnet_sentences_free has 898,161 lines. omcsnet_sentences_more has
2,001,736 lines.
Original downloads are available here
https://github.com/commonsense/conceptnet5/wiki/Downloads. For more
information, see: https://github.com/commonsense/conceptnet5/wiki
The omcsnet data comes with the following warning from the authors of
the above site:
Remember: this data comes from various forms of
crowdsourcing. Sentences in these files are not necessarily true,
useful, or appropriate.
### Languages
en, fr, it, de, es, ru, pt, ja, nl, zh and others
## Dataset Structure
### Data Instances
There are three configurations for the dataset: conceptnet5, omcs_sentences_free, omcs_sentences_more.
Conceptnet5 defines:
``
{
'sentence': ...,
'full_rel': ...,
'rel': ...,
'arg1': ...,
'arg2': ...,
'lang': ...,
'extra_info': ...
'weight': ...
}
``
The omcs text defines:
``
{
'sentence': ...,
'raw_data': ...
'weight': ...
}
``
### Data Fields
For conceptnet5 configurations:
* full_rel: the full relationship. e.g., /a/[/r/Antonym/,/c/en/able/,/c/en/cane/]
* rel: the binary relationship. e.g., /r/Antonym
* arg1: the first argument to the binary relationship. e.g., /c/en/able
* arg2: the second argument to the binary relationship. e.g., /c/en/cane
* lang: the language code. e.g., en, fr, etc. If the arg1 and arg2 are two different languages, then the form os lang1/lang2.
* extra_info: a string that includes json data that has the dataset name, license type (mostly cc-4.0), contributor, etc. e.g., : {"dataset": "/d/verbosity", "license": "cc:by/4.0", "sources": [{"contributor": "/s/resource/verbosity"}], "surfaceEnd": "cane", "surfaceStart": "able", "surfaceText": "[[able]] is the opposite of [[cane]]", "weight": 0.299}
* sentence: the sentence from which the relationship was extracted, if one exists, with brackets around the arg1 and arg2. e.g., [[able]] is the opposite of [[cane]]
* weight: the weight assigned by the curators or automatically to the relationship, between 1.0-0.0, higher being more certain.
For the omcs text configurations:
* sentence: the raw sentence
* raw_data: the raw tab seperated data of the form, id, text, curator_id, created_on, lanugage_id, activity_id, and score. Most of this information was tied to older systems for entering the data os was not partsed into fields for the dataset. e.g., 1237278 someone can be at catch 10805 2006-11-14 17:56:49.70872-05 en 27 1
* lang: the language code
### Data Splits
There are no splits.
## Dataset Creation
### Curation Rationale
This dataset was gathered and created over many years for research in common sense reasoning.
### Source Data
#### Initial Data Collection and Normalization
Started as the Open Mind Common Sense project at MIT Media Lab in 1999. See https://en.wikipedia.org/wiki/Open_Mind_Common_Sense
#### Who are the source language producers?
Crowd Sourced
### Annotations
#### Annotation process
Crowd Source template text, games, etc.
#### Who are the annotators?
Crowd sourced.
### Personal and Sensitive Information
Unkown, but likely there are names of famous individuals.
## Considerations for Using the Data
### Social Impact of Dataset
The goal for the work is to help machines understand common sense.
### Discussion of Biases
See the website and paper for efforts to minimize data bias, but
please note that omcs_sentences_free, omcs_sentences_more are raw data
entered by users and may very well have biased data.
### Other Known Limitations
While the relationship dataset is large, the amount of actual sentences is limited.
## Additional Information
### Dataset Curators
The authors of https://github.com/commonsense/conceptnet5/wiki and Luminoso.
### Licensing Information
This work includes data from ConceptNet 5, which was compiled by the
Commonsense Computing Initiative. ConceptNet 5 is freely available under
the Creative Commons Attribution-ShareAlike license (CC BY SA 3.0) from
http://conceptnet.io.
The included data was created by contributors to Commonsense Computing
projects, contributors to Wikimedia projects, DBPedia, OpenCyc, Games
with a Purpose, Princeton University's WordNet, Francis Bond's Open
Multilingual WordNet, and Jim Breen's JMDict.
Credits and acknowledgements
ConceptNet has been developed by:
The MIT Media Lab, through various groups at different times:
Commonsense Computing
Software Agents
Digital Intuition
The Commonsense Computing Initiative, a worldwide collaboration with contributions from:
National Taiwan University
Universidade Federal de São Carlos
Hokkaido University
Tilburg University
Nihon Unisys Labs
Dentsu Inc.
Kyoto University
Yahoo Research Japan
Luminoso Technologies, Inc.
Significant amounts of data were imported from:
WordNet, a project of Princeton University
Open Multilingual WordNet, compiled by Francis Bond and Kyonghee Paik
Wikipedia and Wiktionary, collaborative projects of the Wikimedia Foundation
Luis von Ahn's "Games with a Purpose"
JMDict, compiled by Jim Breen
CC-CEDict, by MDBG
The Unicode CLDR
DBPedia
Here is a short, incomplete list of people who have made significant contributions to the development of ConceptNet as a data resource, roughly in order of appearance:
Push Singh
Catherine Havasi
Hugo Liu
Hyemin Chung
Robyn Speer
Ken Arnold
Yen-Ling Kuo
Joshua Chin
Joanna Lowry-Duda
Robert Beaudoin
Naoki Otani
Vanya Cohen
Licenses for included resources
Commonsense Computing
The Commonsense Computing project originated at the MIT Media Lab and expanded worldwide. Tens of thousands of contributors have taken some time to teach facts to computers. Their pseudonyms can be found in the "sources" list found in ConceptNet's raw data and in its API.
Games with a Purpose
Data collected from Verbosity, one of the CMU "Games with a Purpose", is used and released under ConceptNet's license, by permission from Luis von Ahn and Harshit Surana.
Verbosity players are anonymous, so in the "sources" list, data from Verbosity is simply credited to the pseudonym "verbosity".
Wikimedia projects
ConceptNet uses data directly from Wiktionary, the free dictionary. It also uses data from Wikipedia, the free encyclopedia via DBPedia.
Wiktionary and Wikipedia are collaborative projects, authored by their respective online communities. They are currently released under the Creative Commons Attribution-ShareAlike license.
Wikimedia encourages giving attribution by providing links to the hosted pages that the data came from, and DBPedia asks for the same thing in turn. In addition to crediting the assertions that came from Wiktionary and DBPedia, we also provide "ExternalURL" edges pointing to the page that they came from. For example, the term /c/de/sprache has an ExternalURL link pointing to http://en.wiktionary.org/wiki/Sprache. Its list of individual contributors can be seen by following its "History" link.
The URLs of links to DBPedia are the same as the resource names that DBPedia uses, encouraging interoperability with their linked data.
WordNet
WordNet is available under an unencumbered license: see http://wordnet.princeton.edu/wordnet/license/. Its text is reproduced below:
WordNet Release 3.0
This software and database is being provided to you, the LICENSEE, by Princeton University under the following license. By obtaining, using and/or copying this software and database, you agree that you have read, understood, and will comply with these terms and conditions.:
Permission to use, copy, modify and distribute this software and database and its documentation for any purpose and without fee or royalty is hereby granted, provided that you agree to comply with the following copyright notice and statements, including the disclaimer, and that the same appear on ALL copies of the software, database and documentation, including modifications that you make for internal use or for distribution.
WordNet 3.0 Copyright 2006 by Princeton University. All rights reserved.
THIS SOFTWARE AND DATABASE IS PROVIDED "AS IS" AND PRINCETON UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PRINCETON UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES OF MERCHANT- ABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE, DATABASE OR DOCUMENTATION WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER RIGHTS.
The name of Princeton University or Princeton may not be used in advertising or publicity pertaining to distribution of the software and/or database. Title to copyright in this software, database and any associated documentation shall at all times remain with Princeton University and LICENSEE agrees to preserve same.
Open Multilingual WordNet
Open Multilingual WordNet was compiled by Francis Bond, Kyonghee Paik, and Ryan Foster, from data provided by many multilingual WordNet projects. Here is the complete list of references to the projects that created the data.
### Citation Information
```
@paper{speer2017conceptnet,
author = {Robyn Speer and Joshua Chin and Catherine Havasi},
title = {ConceptNet 5.5: An Open Multilingual Graph of General Knowledge},
conference = {AAAI Conference on Artificial Intelligence},
year = {2017},
pages = {4444--4451},
keywords = {ConceptNet; knowledge graph; word embeddings},
url = {http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14972}
}
```
### Contributions
Thanks to [@ontocord](https://github.com/ontocord) for adding this dataset. |