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"usually , he would be tearing around the living room , playing with his toys ."
"but just one look at a minion sent him practically catatonic ."
"that had been megan 's plan when she got him dressed earlier ."
"he 'd seen the movie almost by mistake , considering he was a little young for the pg cartoon , but with older cousins , along with her brothers , mason was often exposed to things that were older ."
"she liked to think being surrounded by adults and older kids was one reason why he was a such a good talker for his age ."
"`` are n't you being a good boy ? ''"
"she said ."
"mason barely acknowledged her ."
"instead , his baby blues remained focused on the television ."
"since the movie was almost over , megan knew she better slip into the bedroom and finish getting ready ."
"each time she looked into mason 's face , she was grateful that he looked nothing like his father ."
"his platinum blond hair and blue eyes were completely hers ."
"it was only his build that he was taking after his father ."
"where megan was a diminutive 5'3 '' , davis was 6'1 '' and two hundred pounds ."
"mason was already registering off the charts in height and weight according to his pediatrician ."
"davis had seen mason only twice in his lifetime-the day he had been born and the day he came home from the hospital ."
"after that , he had n't been interested in any of the pictures and emails megan sent ."
"with his professional football career on the rise , davis had n't wanted to be shackled with the responsibilities of a baby ."
"instead , he wanted to spend his time off the field partying until all hours of the night ."
"he only paid child support when megan threatened to have his wages garnished ."
"she dreaded the day when mason was old enough to ask about his father ."
"she never wanted anything in the world to hurt him , and she knew that being rejected by his father would ."
"with a sigh , she stepped into the dress and slid it over her hips ."
"wrestling around to get the zipper all the way up caused her to huff and puff ."
"standing back from the mirror , she turned to and fro to take in her appearance ."
"she 'd always loved how the dress made her feel sexy , but at the same time was very respectable ."
"while it boasted a sweetheart neckline , the hemline fell just below her knees ."
"she put on her pearls-a high school graduation gift from her uncle aidan , or `` ankle '' , as she often called him ."
"aidan was her mother 's baby brother and only son of the family ."
"when she was born , he was only eight and a half ."
"as the first grandchild , megan spent a lot of time with her grandparents , and that in turn , meant she spent a lot of time with aidan ."
"he had devoted hours to holding her and spoiling her rotten ."
"when it came time for her to talk , she just could n't seem to get `` uncle aidan '' out ."
"instead , she called him `` ankle . ''"
"it was a nickname that had stuck with him even now that he was thirty-four and married ."
"while it had been no question that she wanted him as godfather for mason , she had been extremely honored when he and his wife , emma , had asked her to be their son , noah 's , godmother ."
"she loved her newest cousin very much and planned to be the best godmother she could for him ."
"as she stepped out of the bedroom , she found that mason had yet to move ."
"`` okay buddy , time to go . ''"
"when he started to whine , she shook her head ."
"`` we have such a fun day ahead of us ."
"it 's noah 's baptism , and then there 's a party at uncle aidan and aunt emma 's house . ''"
"`` beau ? ''"
"he asked ."
"she laughed ."
"`` yes , you 'll get to see and play with beau , too . ''"
"as she went to the couch and picked him up , she could n't help finding it amusing that out of everyone he was going to see today , he was most excited about being with aidan and emma 's black lab , beau ."
"one day when they had their own place again , she would get him a dog ."
"he loved them too much to be denied ."
"`` oomph , '' she muttered , as they started up the basement stairs ."
"`` heawy ? ''"
"he asked ."
"`` yes , you 're getting to be such a big , heavy boy . ''"
"when they made it to the kitchen , megan paused to catch her breath ."
"she only had a second before her mother breezed in with sean , and her youngest brother , gavin ."
"`` ready ? ''"
"she asked ."
"megan nodded ."
"feeling like she was once again a teenager , she filed behind her parents as they headed into the garage ."
"`` i want to drive , '' gavin said ."
"with a smirk , sean replied , `` like i 'm gon na let you drive my car . ''"
"he then slid into the driver 's seat as gavin reluctantly walked around to the passenger 's side ."
"`` we 'll see you there in just a few , '' her mother called ."
"sean acknowledged her with a two finger salute before cranking up and pulling down the driveway ."
"megan worked to get mason into the car seat in her parents ' land rover ."
"once he was safely strapped and buckled in , she hopped in beside him ."
"her parents rattled along to each other as they made their way through the tree-lined suburbs where megan had grown up ."
"while some might look on her as having a mark against her character being an unwed mother , she had lived a relatively non-rebellious life ."
"even though she 'd been a cheerleader and ran with the popular crowd in school , she rarely partied to excess ."
"instead , she had focused on getting good grades ."
"at that time , she had her heart set on going to medical school and becoming a doctor ."
"from the time she was a little girl , she had wanted nothing more than to help people ."
"she was always mending birds with broken wings or trying to resuscitate squirrels who had been hit by cars ."
"she ditched playing princess for playing `` hospital . ''"
"her desire to become a doctor was why she needed the best scores and best activities and why she generally shunned any temptations to lead her off the right path ."
"she had even managed to bypass the usual freshman craziness when she went off to the university of georgia ."
"it was n't until she fell in love for the first time in her life that she threw everything away ."
"sadly , she could n't say that her first love was davis , mason 's father ."
"instead , it was another football player , this time a running back at uga , who captured and later broke her heart a year later ."
"carsyn ran with the fast crowd , and when she was with him , she partied and drank too much ."
"he was controlling and possessive , and he wanted all of her time ."
"when she was with him , she had little time for studying ."
"with her grades already in the toilet , she was unprepared for the emotional breakdown she experienced when carsyn broke up with her ."
"devastated , she stopped going to class and ended up flunking the semester ."
"by the time she got back on track with her grades , she had abandoned any hope of medical school ."
"instead , she decided that she would become a nurse , which would fulfill her need to care for sick people ."
"of course , her relationship with davis ended up derailing shortly before graduation when she got pregnant unexpectedly ."
"she had to take several semesters off after mason was born ."
"she was a few years off from when she had originally planned on graduating , but she was excited after everything had that had happened , she was finally finishing ."
"her mother 's voice brought megan out of her thoughts ."
"`` here we are , '' she said pleasantly ."
"leaning forward in her seat , megan eyed the clock on the dashboard ."
"she was n't surprised to see they had arrived half an hour before the baptism started ."
"one thing her mother prided herself on was being on time and lending a hand ."
"as they started into the church , her mother reached for mason ."
"`` we 'll take him so you can go see if emma needs any help . ''"
"megan bent over to kiss mason 's cheek ."
"`` see you in a little while , sweetie . ''"
"he grinned and then happily dodged her mother 's arms for her father 's instead , which made megan smile ."
"he was such a man 's man already ."
End of preview (truncated to 100 rows)

Dataset Card for BookCorpus

Dataset Summary

Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story.This work aims to align books to their movie releases in order to providerich descriptive explanations for visual content that go semantically farbeyond the captions available in current datasets.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

plain_text

  • Size of downloaded dataset files: 1124.87 MB
  • Size of the generated dataset: 4629.00 MB
  • Total amount of disk used: 5753.87 MB

An example of 'train' looks as follows.

{
    "text": "But I traded all my life for some lovin' and some gold"
}

Data Fields

The data fields are the same among all splits.

plain_text

  • text: a string feature.

Data Splits

name train
plain_text 74004228

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

The books have been crawled from https://www.smashwords.com, see their terms of service for more information.

A data sheet for this dataset has also been created and published in Addressing "Documentation Debt" in Machine Learning Research: A Retrospective Datasheet for BookCorpus.

Citation Information

@InProceedings{Zhu_2015_ICCV,
    title = {Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books},
    author = {Zhu, Yukun and Kiros, Ryan and Zemel, Rich and Salakhutdinov, Ruslan and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
    month = {December},
    year = {2015}
}

Contributions

Thanks to @lewtun, @richarddwang, @lhoestq, @thomwolf for adding this dataset.

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