File size: 17,053 Bytes
748114f 74daf18 748114f 74daf18 07db6a1 748114f 85c7432 93f534d 2e57021 03748f2 e995fd5 03748f2 748114f 2e57021 748114f 93f534d 748114f 93f534d 748114f 852ca31 748114f 5982ae9 748114f 2e57021 748114f 2e57021 748114f 2e57021 748114f 2e57021 852ca31 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 |
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
paperswithcode_id: totto
pretty_name: ToTTo
dataset_info:
features:
- name: id
dtype: int32
- name: table_page_title
dtype: string
- name: table_webpage_url
dtype: string
- name: table_section_title
dtype: string
- name: table_section_text
dtype: string
- name: table
list:
list:
- name: column_span
dtype: int32
- name: is_header
dtype: bool
- name: row_span
dtype: int32
- name: value
dtype: string
- name: highlighted_cells
sequence:
sequence: int32
- name: example_id
dtype: string
- name: sentence_annotations
sequence:
- name: original_sentence
dtype: string
- name: sentence_after_deletion
dtype: string
- name: sentence_after_ambiguity
dtype: string
- name: final_sentence
dtype: string
- name: overlap_subset
dtype: string
splits:
- name: train
num_bytes: 652754806
num_examples: 120761
- name: validation
num_bytes: 47277039
num_examples: 7700
- name: test
num_bytes: 40883586
num_examples: 7700
download_size: 187724372
dataset_size: 740915431
---
# Dataset Card for ToTTo
## 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:** None
- **Repository:** https://github.com/google-research-datasets/ToTTo
- **Paper:** https://arxiv.org/abs/2004.14373
- **Leaderboard:** https://github.com/google-research-datasets/ToTTo#leaderboard
- **Point of Contact:** [[email protected]](mailto:[email protected])
### Dataset Summary
ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled
generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
A sample training set is provided below
```
{'example_id': '1762238357686640028',
'highlighted_cells': [[13, 2]],
'id': 0,
'overlap_subset': 'none',
'sentence_annotations': {'final_sentence': ['A Favorita is the telenovela aired in the 9 pm timeslot.'],
'original_sentence': ['It is also the first telenovela by the writer to air in the 9 pm timeslot.'],
'sentence_after_ambiguity': ['A Favorita is the telenovela aired in the 9 pm timeslot.'],
'sentence_after_deletion': ['It is the telenovela air in the 9 pm timeslot.']},
'table': [[{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': '#'},
{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Run'},
{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Title'},
{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Chapters'},
{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Author'},
{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Director'},
{'column_span': 1,
'is_header': True,
'row_span': 1,
'value': 'Ibope Rating'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '59'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'June 5, 2000— February 2, 2001'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Laços de Família'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Manoel Carlos'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Ricardo Waddington'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '44.9'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '60'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'February 5, 2001— September 28, 2001'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Porto dos Milagres'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Aguinaldo Silva Ricardo Linhares'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Marcos Paulo Simões'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '44.6'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '61'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'October 1, 2001— June 14, 2002'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'O Clone'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Glória Perez'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Jayme Monjardim'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '47.0'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '62'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'June 17, 2002— February 14, 2003'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Esperança'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Benedito Ruy Barbosa'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Luiz Fernando'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '37.7'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '63'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'February 17, 2003— October 10, 2003'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Mulheres Apaixonadas'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Manoel Carlos'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Ricardo Waddington'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.6'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '64'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'October 13, 2003— June 25, 2004'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Celebridade'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Gilberto Braga'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Dennis Carvalho'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.0'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '65'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'June 28, 2004— March 11, 2005'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Senhora do Destino'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Aguinaldo Silva'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Wolf Maya'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '50.4'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '66'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'March 14, 2005— November 4, 2005'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'América'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Glória Perez'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Jayme Monjardim Marcos Schechtman'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '49.4'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '67'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'November 7, 2005— July 7, 2006'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Belíssima'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Sílvio de Abreu'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Denise Saraceni'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '48.5'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '68'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'July 10, 2006— March 2, 2007'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Páginas da Vida'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Manoel Carlos'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Jayme Monjardim'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.8'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '69'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'March 5, 2007— September 28, 2007'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Paraíso Tropical'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '179'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Gilberto Braga Ricardo Linhares'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Dennis Carvalho'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '42.8'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '70'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'October 1, 2007— May 31, 2008'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Duas Caras'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '210'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Aguinaldo Silva'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Wolf Maya'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '41.1'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '71'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'June 2, 2008— January 16, 2009'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'A Favorita'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '197'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'João Emanuel Carneiro'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Ricardo Waddington'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '39.5'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '72'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'January 19, 2009— September 11, 2009'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Caminho das Índias'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Glória Perez'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Marcos Schechtman'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '38.8'}],
[{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '73'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'September 14, 2009— May 14, 2010'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Viver a Vida'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Manoel Carlos'},
{'column_span': 1,
'is_header': False,
'row_span': 1,
'value': 'Jayme Monjardim'},
{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '35.6'}]],
'table_page_title': 'List of 8/9 PM telenovelas of Rede Globo',
'table_section_text': '',
'table_section_title': '2000s',
'table_webpage_url': 'http://en.wikipedia.org/wiki/List_of_8/9_PM_telenovelas_of_Rede_Globo'}
```
Please note that in test set sentence annotations are not available and thus values inside `sentence_annotations` can be safely ignored.
### Data Fields
- `table_webpage_url` (`str`): Table webpage URL.
- `table_page_title` (`str`): Table metadata with context about the table.
- `table_section_title` (`str`): Table metadata with context about the table.
- `table_section_text` (`str`): Table metadata with context about the table.
- `table` (`List[List[Dict]]`): The outer lists represents rows and the inner lists columns. Each Dict has the fields:
- `column_span` (`int`)
- `is_header` (`bool`)
- `row_span` (`int`)
- `value` (`str`)
- `highlighted_cells` (`List[[row_index, column_index]]`): Where each `[row_index, column_index]` pair indicates that `table[row_index][column_index]` is highlighted.
- `example_id` (`int`): A unique id for this example.
- `sentence_annotations`: Consists of the `original_sentence` and the sequence of revised sentences performed in order to produce the `final_sentence`.
### Data Splits
```
DatasetDict({
train: Dataset({
features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
num_rows: 120761
})
validation: Dataset({
features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
num_rows: 7700
})
test: Dataset({
features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
num_rows: 7700
})
})
```
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
[More Information Needed]
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
[More Information Needed]
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```
@inproceedings{parikh2020totto,
title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
booktitle={Proceedings of EMNLP},
year={2020}
}
```
### Contributions
Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset. |