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"""The Caption Contest benchmark.""" |
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import json |
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import os |
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import datasets |
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import base64 |
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import pprint |
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_CAPTION_CONTEST_TASKS_CITATION = """\ |
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@article{hessel2022androids, |
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title={Do Androids Laugh at Electric Sheep? Humor" Understanding" Benchmarks from The New Yorker Caption Contest}, |
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author={Hessel, Jack and Marasovi{\'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin}, |
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journal={arXiv preprint arXiv:2209.06293}, |
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year={2022} |
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} |
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www.capcon.dev |
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Our data contributions are: |
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- The cartoon-level annotations; |
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- The joke explanations; |
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- and the framing of the tasks |
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We release these data we contribute under CC-BY (see DATASET_LICENSE). |
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If you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived: |
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@misc{newyorkernextmldataset, |
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author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott}, |
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title={The {N}ew {Y}orker Cartoon Caption Contest Dataset}, |
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year={2020}, |
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url={https://nextml.github.io/caption-contest-data/} |
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} |
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@inproceedings{radev-etal-2016-humor, |
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title = "Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest", |
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author = "Radev, Dragomir and |
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Stent, Amanda and |
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Tetreault, Joel and |
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Pappu, Aasish and |
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Iliakopoulou, Aikaterini and |
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Chanfreau, Agustin and |
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de Juan, Paloma and |
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Vallmitjana, Jordi and |
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Jaimes, Alejandro and |
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Jha, Rahul and |
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Mankoff, Robert", |
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booktitle = "LREC", |
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year = "2016", |
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} |
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@inproceedings{shahaf2015inside, |
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title={Inside jokes: Identifying humorous cartoon captions}, |
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author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert}, |
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booktitle={KDD}, |
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year={2015}, |
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} |
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""" |
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_CAPTION_CONTEST_DESCRIPTION = """\ |
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There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality |
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of that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny. |
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""" |
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_MATCHING_DESCRIPTION = """\ |
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You are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it. |
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""" |
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_RANKING_DESCRIPTION = """\ |
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You are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it. |
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""" |
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_EXPLANATION_DESCRIPTION = """\ |
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You are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation. |
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""" |
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_IMAGES_URL = "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip" |
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def _get_configs_crossvals(): |
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cross_val_configs = [] |
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for split_idx in [1,2,3,4]: |
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cur_split_configs = [ |
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CaptionContestConfig( |
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name='matching_{}'.format(split_idx), |
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description=_MATCHING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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], |
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label_classes=["A", "B", "C", "D", "E"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='matching_from_pixels_{}'.format(split_idx), |
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description=_MATCHING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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], |
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label_classes=["A", "B", "C", "D", "E"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='ranking_{}'.format(split_idx), |
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description=_RANKING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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'winner_source', |
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], |
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label_classes=["A", "B"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='ranking_from_pixels_{}'.format(split_idx), |
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description=_RANKING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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'winner_source', |
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], |
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label_classes=["A", "B"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='explanation_{}'.format(split_idx), |
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description=_EXPLANATION_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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], |
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label_classes=None, |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='explanation_from_pixels_{}'.format(split_idx), |
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description=_EXPLANATION_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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], |
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label_classes=None, |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_{}.zip'.format(split_idx), |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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] |
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cross_val_configs.extend(cur_split_configs) |
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return cross_val_configs |
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class CaptionContestConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Caption Contest.""" |
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def __init__(self, features, data_url, citation, url, label_classes=None, **kwargs): |
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"""BuilderConfig for Caption Contest. |
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Args: |
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features: `list[string]`, list of the features that will appear in the |
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feature dict. Should not include "label". |
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data_url: `string`, url to download the zip file from. |
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citation: `string`, citation for the data set. |
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url: `string`, url for information about the data set. |
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label_classes: `list[string]`, the list of classes for the label if the |
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label is present as a string. If not provided, there is no fixed label set. |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(CaptionContestConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.features = features |
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self.data_url = data_url |
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self.citation = citation |
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self.url = url |
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self.label_classes = label_classes |
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class CaptionContest(datasets.GeneratorBasedBuilder): |
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"""The CaptionContest benchmark.""" |
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BUILDER_CONFIGS = [ |
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CaptionContestConfig( |
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name='matching', |
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description=_MATCHING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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], |
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label_classes=["A", "B", "C", "D", "E"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='matching_from_pixels', |
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description=_MATCHING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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], |
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label_classes=["A", "B", "C", "D", "E"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='ranking', |
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description=_RANKING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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'winner_source', |
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], |
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label_classes=["A", "B"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='ranking_from_pixels', |
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description=_RANKING_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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'winner_source', |
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], |
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label_classes=["A", "B"], |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='explanation', |
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description=_EXPLANATION_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'image_location', |
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'image_description', |
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'image_uncanny_description', |
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'entities', |
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'questions', |
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'caption_choices', |
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'from_description', |
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], |
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label_classes=None, |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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CaptionContestConfig( |
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name='explanation_from_pixels', |
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description=_EXPLANATION_DESCRIPTION, |
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features=[ |
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'image', |
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'contest_number', |
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'caption_choices', |
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], |
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label_classes=None, |
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data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels.zip', |
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url='www.capcon.dev', |
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citation=_CAPTION_CONTEST_TASKS_CITATION, |
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), |
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] + _get_configs_crossvals() |
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def _info(self): |
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features = {feature: datasets.Value("string") for feature in self.config.features} |
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features['contest_number'] = datasets.Value("int32") |
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if 'explanation' not in self.config.name: |
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features['caption_choices'] = datasets.features.Sequence(datasets.Value("string")) |
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if 'entities' in features: |
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features['entities'] = datasets.features.Sequence(datasets.Value("string")) |
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if 'questions' in features: |
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features['questions'] = datasets.features.Sequence(datasets.Value("string")) |
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if 'image' in features: |
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features['image'] = datasets.Image() |
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features['label'] = datasets.Value("string") |
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features['n_tokens_label'] = datasets.Value("int32") |
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features['instance_id'] = datasets.Value("string") |
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return datasets.DatasetInfo( |
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description=_CAPTION_CONTEST_DESCRIPTION + self.config.description, |
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features=datasets.Features(features), |
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homepage=self.config.url, |
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citation=self.config.citation |
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) |
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def _split_generators(self, dl_manager): |
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dl_dir = dl_manager.download_and_extract(self.config.data_url) or "" |
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self.images_dir = dl_manager.download_and_extract(_IMAGES_URL) |
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task_name = _get_task_name_from_data_url(self.config.data_url) |
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dl_dir = os.path.join(dl_dir, task_name) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_file": os.path.join(dl_dir, "train.jsonl"), |
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"split": datasets.Split.TRAIN, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"data_file": os.path.join(dl_dir, "val.jsonl"), |
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"split": datasets.Split.VALIDATION, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_file": os.path.join(dl_dir, "test.jsonl"), |
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"split": datasets.Split.TEST, |
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}, |
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), |
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] |
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def _generate_examples(self, data_file, split): |
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with open(data_file, encoding="utf-8") as f: |
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for line in f: |
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row = json.loads(line) |
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with open(self.images_dir + "/all_contest_images/{}.jpeg".format(row['contest_number']), "rb") as image: |
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row['image'] = {"path": self.images_dir + "/all_contest_images/{}.jpeg".format(row['contest_number']), |
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"bytes": image.read()} |
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yield row['instance_id'], row |
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def _get_task_name_from_data_url(data_url): |
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return data_url.split("/")[-1].split(".")[0] |
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|
