Sold by: Amazon
Open data
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Deployed on AWS
This dataset provides labeled humor detection from product question answering systems.
The dataset contains 3 csv files: [Humorous.csv](https://humor-detection-pds.s3-us-west-2.amazonaws.com/Humorous.csv)
containing the humorous product questions,
[Non-humorous-unbiased.csv](https://humor-detection-pds.s3-us-west-2.amazonaws.com/Non-humorous-unbiased.csv) containing
the non-humorous prodcut questions from the same products as the humorous one, and,
[Non-humorous-biased.csv](https://humor-detection-pds.s3-us-west-2.amazonaws.com/Non-humours-biased.csv) containing
the non-humorous prodcut questions from randomly selected products.
Each file has the question, product description, image url to the product,
and a label if the question is humorous or not.
Overview
This dataset provides labeled humor detection from product question answering systems. The dataset contains 3 csv files: Humorous.csv containing the humorous product questions, Non-humorous-unbiased.csv containing the non-humorous prodcut questions from the same products as the humorous one, and, Non-humorous-biased.csv containing the non-humorous prodcut questions from randomly selected products. Each file has the question, product description, image url to the product, and a label if the question is humorous or not.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Humor Detection Dataset
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::humor-detection-pds
- AWS region
- us-west-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://humor-detection-pds/
Resources
Vendor resources
Support
Contact
Managed By
How to cite
Humor Detection from Product Question Answering Systems was accessed on DATE from https://registry.opendata.aws/humor-detection .
License
Similar products
This dataset provides a set of non-shoppable items, which are items that can't be purchased via a virtual assistant (love, vampires, etc).
In addition, for each non-shoppable item, the dataset contains humorous responses generated by two different large language models, and a template-based generation solution that uses a commonsense knowledge graph called ConceptNet.
Finally, each row contains a score provided by human annotators that judge how funny each response is.
The columns provided for each datapoint are as follows:
question- purchase request of the non-shoppable item
answer- a generated response
model- the name of the model or solution that generated the response
nonshoppableitem- the name of the non shoppable item
relation- commonsense relation that was used to generate the response in the template-based approach
promptortemplate- the prompt that was used to generate the responses
score- the average response score of the human evaluation
Humor patterns used for querying Alexa traffic when creating the taxonomy described in the paper "“Alexa, Do You Want to Build a Snowman?” Characterizing Playful Requests to Conversational Agents" by Shani C., Libov A., Tolmach S., Lewin-Eytan L., Maarek Y., and Shahaf D. (CHI LBW 2022). These patterns corrospond to the researchers' hypotheses regarding what humor types are likely to appear in Alexa traffic. These patterns were used for querying Alexa traffic to evaluate these hypotheses.
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mixture of experts (MoE) architecture that supports multiple languages, primarily English and Japanese