Developing Models to Identify Inconsistent Statements in Machine Learning
In the realm of language processing and product retrieval systems, Amazon has developed a unique dataset aimed at identifying counterfactual statements. This dataset, specific to English, German, and Japanese, is not directly linked in public search results, but here's a step-by-step guide on how to access it.
- Amazon Counterfactual Datasets and Research
A 2025 paper discusses Amazon datasets used for counterfactual explanations in recommender systems, but it does not specify language coverage for our target languages [1]. Another Amazon research paper focuses on counterfactual learning to rank, involving sequential user search behavior rather than a multilingual counterfactual text dataset [2].
- Datasets involving Amazon Product Reviews or Annotations
A dataset related to Amazon product reviews annotated for sarcasm (in English) and relation detection is mentioned, but it does not involve German or Japanese languages or counterfactual statements specifically [3].
- Access via Amazon’s Data Platforms
Amazon SageMaker and AWS Data Wrangler tools offer ways to import datasets from Amazon S3 buckets or AWS catalogs. However, these tools require you to have permissions and access to the dataset location, which does not clarify if the counterfactual dataset in multiple languages exists there or is publicly accessible [4].
How to proceed for access:
- Check Amazon Scientific Research webpages or Amazon Open Data portals to see if a multilingual counterfactual dataset is published. Such datasets are typically hosted on academic repositories (e.g., arXiv, datasets on GitHub linked from papers) or Amazon’s own data portals.
- Review the authorship of the counterfactual-related papers (e.g., those from Delft University or Amazon Science) and contact the authors for data access or additional instructions. Public datasets are often shared upon request or in supplementary material of the papers [1][2].
- If you are an AWS user, explore the Amazon SageMaker Data Wrangler to connect to Amazon S3 buckets that may contain the dataset if you have appropriate permissions [4].
- Look specifically for multilingual NLP datasets from Amazon (English, German, Japanese) by querying Amazon’s research publications or dataset repositories.
The dataset also includes annotations for the counterfactual statements. It is used to improve product retrieval systems by identifying misleading counterfactual statements and is designed to help language processing models understand the structure of counterfactual statements, containing words commonly found in counterfactual statements, such as "wished" and "except." Amazon has developed this dataset for training language processing models to identify counterfactual statements.
While a direct public link or source for an Amazon dataset of counterfactual statements in English, German, and Japanese was not found in the returned results, you may need to identify the specific research paper or project that released this dataset and request access through those channels. Usage of Amazon SageMaker tools can facilitate import if you already have dataset storage access.
- The dataset developed by Amazon for training language processing models to identify counterfactual statements might not be directly accessible through public search results, but it can be discovered by checking Amazon Scientific Research webpages, academic repositories like arXiv, or Amazon Open Data portals.
- The counterfactual dataset created by Amazon for multiple languages (English, German, Japanese) can be found either through connections made with the authors of relevant research papers (such as those from Delft University or Amazon Science) or by exploring the Amazon SageMaker Data Wrangler to connect to Amazon S3 buckets with the appropriate permissions.
