Dataset research report
Banking77 research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Dataset Card for BANKING77 Dataset Summary Deprecated: Dataset "banking77" is deprecated and will be deleted. Use "PolyAI/banking77" instead. Dataset composed of online banking queries annotated with their corresponding intents. BANKING77 dataset provides a very fine-grained set of intents in a banking domain. It comprises 13,083 customer service queries labeled with 77 intents. It focuses on fine-grained single-domain intent detection. Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/legacy-datasets/banking77.
Research Context
Banking77: 500 rows by 2 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Data Profile
Chart Evidence
These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.
Follow-Up Queries
Preview Rows
| # | texttext | labelinteger |
|---|---|---|
| 1 | I am still waiting on my card? | 11 |
| 2 | What can I do if my card still hasn't arrived after 2 weeks? | 11 |
| 3 | I have been waiting over a week. Is the card still coming? | 11 |
| 4 | Can I track my card while it is in the process of delivery? | 11 |
| 5 | How do I know if I will get my card, or if it is lost? | 11 |
| 6 | When did you send me my new card? | 11 |
Data Dictionary
- text text
- label numeric
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.