---
license: unknown
language:
- en
task_categories:
- text-generation
- question-answering
- text-classification
size_categories:
- 10K<n<100K
pretty_name: GTBank Customer Service Synthetic Dataset
tags:
- customer-service
- banking
- nigeria
- synthetic
- intent-classification
- dialogue
---

# GTBank Customer Service Synthetic Dataset

## Overview

This dataset contains 15,000 synthetic customer-service exchanges modeled on a Nigerian retail bank (GTBank), each pairing a customer `user_query` with an `assistant_reply` and an `intent` label (e.g. PIN change, account restriction, card activation, BVN issues). All content verified in this file is in **English**; no other languages (e.g. Nigerian Pidgin, Hausa, Igbo) were found in the data despite the repository name.

**Note on repository name:** the repo is named `translate_this`, but on inspection the single data file it contains is not a translation corpus — there are no source/target language pairs. It is a monolingual (English) customer-support intent/response dataset. This card describes the data as it actually exists in the repository.

## Dataset Structure

The dataset consists of a single JSON Lines file, `gtbank_customer_service_synthetic_15k.jsonl`, with **15,000 rows** (verified by direct line count). Each row is a JSON object with the following fields:

| Field | Type | Description |
|---|---|---|
| `id` | string | Unique record identifier (e.g. `gtb_cs_00001`). All 15,000 ids are unique. |
| `timestamp` | string | ISO-8601 datetime stamp on the record, ranging from `2022-01-01T01:53:00` to `2025-12-31T22:27:00`. |
| `year` | integer | Year extracted from the timestamp (2022–2025, roughly evenly distributed: ~3,660–3,810 rows per year). |
| `user_query` | string | A customer's banking support question (average length ~50 characters). |
| `assistant_reply` | string | The corresponding support response, sometimes containing markdown formatting (e.g. `**bold**`) (average length ~173 characters). |
| `intent` | string | One of 16 intent categories labeling the topic of the exchange. |

The 16 observed intent categories are: `account_opening`, `account_restriction`, `beneficiary_issues`, `bvn_issues`, `card_activation`, `card_block_unblock`, `chargeback_dispute`, `debit_alerts`, `failed_transfer_debit`, `nin_linking`, `password_reset`, `pin_change`, `statement_request`, `transfer_limits`, `usd_card_fx`, `ussd_help`.

**Language pair(s) observed:** none — this is a monolingual English dataset, not a translation dataset.

**Important duplication note:** while there are 15,000 rows, there are only **1,816 unique `(user_query, assistant_reply)` pairs**. Each underlying Q&A pair is repeated multiple times (roughly 8x on average) under different `id`/`timestamp`/`year` values. Users training on this data should be aware of this templated repetition rather than assuming 15,000 unique conversations.

## Data Format

A single UTF-8 encoded JSON Lines (`.jsonl`) file, one JSON object per line, ~5.2 MB in size. No other files are present in the repository besides `.gitattributes`.

## Intended Use

Given the verified content, this dataset is best suited for:
- Fine-tuning or evaluating conversational/customer-support response generation models for banking use cases.
- Intent classification training, using `user_query` (or `user_query` + `assistant_reply`) against the `intent` label.

It is **not** suitable as-is for machine translation model training, since no translation pairs exist in the data currently hosted in this repository.

## Limitations

- **Not a translation dataset**: despite the repository name (`translate_this`), the hosted file contains no source/target language pairs. This appears to be a work-in-progress or mislabeled repository rather than a finished translation corpus.
- **Synthetic data**: both queries and replies appear to be synthetically generated (or templated) rather than sourced from real customer interactions, so it may not fully reflect real-world phrasing, noise, or edge cases.
- **High duplication**: only ~1,816 unique query/reply pairs underlie the 15,000 rows, so effective content diversity is much lower than the row count suggests.
- **Single language**: only English content was verified; no multilingual or code-switched (e.g. Pidgin) text was found.
- **Unverified license and provenance**: no license file or documentation accompanies the dataset, and GTBank does not appear to be an official data provider — treat content as illustrative/synthetic rather than authoritative banking guidance.

## Author

Curated by [Ephraimmm](https://huggingface.co/Ephraimmm)