Gridexis/assistant-dialogue-pairs-13k

Assistant Dialogue Pairs 13K — English Two-Turn Conversations

Release status: review required. This package is technically prepared for Hugging Face Dataset Viewer and datasets, but should remain private or gated until the maintainer has documented the right to redistribute and permit the intended use of every record. The other license tag is intentional: this package is not offered under Apache-2.0 or another blanket permissive license.

Dataset Description

Assistant Dialogue Pairs 13K is a collection of English, two-turn user–assistant conversations. Every record contains exactly one user message followed by one assistant message. The package is intended for controlled research, data-quality inspection, and evaluation of conversational-data pipelines within the limits stated in LICENSE.

The public release deliberately does not claim that individual records originate from, are endorsed by, or are licensed by any particular AI provider. Internal source labels were replaced with neutral collection_batch values. The maintainer should keep a private, auditable provenance log before enabling public access.

Property	Value
Release version	0.1.0-rc1
Records after exact deduplication	13,178
Language	English (en)
Structure	Two turns: user → assistant
Splits	11,804 train / 695 validation / 679 test
Format	UTF-8 JSON Lines
Dataset Viewer	Configured through YAML data_files
License status	other; controlled research only pending rights review

Data Schema

{
  "id": "adp-000001",
  "messages": [
    {"role": "user", "content": "..."},
    {"role": "assistant", "content": "..."}
  ],
  "language": "en",
  "subset": "general",
  "collection_batch": "batch_01",
  "quality_status": "format_validated_and_redacted",
  "provenance_status": "release_review_required"
}

Field	Type	Description
id	string	Stable release identifier.
messages	list of objects	Ordered messages with role and content.
language	string	Language label for this release.
subset	string	Broad content group: general, smalltalk, or mixed_tasks.
collection_batch	string	Neutral batch identifier. It is not a model-identity claim.
quality_status	string	Indicates structural validation and specified redaction; not a correctness guarantee.
provenance_status	string	Signals that rights/provenance review is required before open redistribution.

Splits

The split is deterministic and group-aware: all records with the same normalized user prompt are placed in the same split. This reduces prompt leakage between training and development splits. These splits are not independent benchmarks and must not be used to make general capability claims.

Split	Rows
train	11,804
validation	695
test	679

Data Processing

The release builder performed the following steps:

1. Parsed each non-empty source line as JSON and required exactly two non-empty messages ordered as user, then assistant.
2. Removed exact duplicate prompt–response pairs after whitespace normalization.
3. Redacted e-mail addresses, Luhn-valid payment-card numbers, and token-like strings. This resulted in 2 e-mail, 1 payment-card, and 0 token redactions.
4. Replaced original file labels with neutral collection-batch labels in public data.
5. Created deterministic prompt-grouped splits and re-parsed every exported JSONL row.

The source mapping and collection evidence are intentionally not published in this release candidate. The maintainer must preserve them privately and use them to decide whether the repository may become public.

Intended Uses

This release candidate is suitable for validating a JSONL-based conversational-dataset pipeline, running private data-quality review, and conducting controlled research under the documented rights limitations. It is not yet suitable as a generally reusable public SFT corpus or as a source for commercial model development.

Limitations and Risks

Responses can be incomplete, factually incorrect, biased, repetitive, or unsafe. The set is short, English-language, and predominantly two-turn; it is not representative of real-world dialogue or a provider’s production behaviour. The card does not establish rights in the inputs or outputs. Source service terms, upstream licenses, personal-data obligations, and any third-party rights remain controlling.

Licensing and Access

The repository must remain private or gated until a rights review confirms that the intended public use is allowed for all included records. Do not mark this dataset apache-2.0, mit, cc0-1.0, or cc-by-4.0 merely to improve discoverability. A public Hugging Face repository grants downstream users broad access and re-use rights through the service, so the selected license must match documented rights for the whole dataset.1 2

Loading

from datasets import load_dataset

# Replace with the actual repository ID after upload.
ds = load_dataset("Gridexis/assistant-dialogue-pairs-13k", "default")
print(ds)
print(ds["train"][0]["messages"])

Files

File	Purpose
data/*.jsonl	Viewer-compatible split files.
QUALITY.md	Validation, redaction, and deduplication report.
SCHEMA.md	Stable public schema.
PROVENANCE.md	Release constraints and private evidence requirements.
TRAINING.md	Safe loading guidance.
manifest.json	Checksums and row counts for this package.
CHANGELOG.md	Version history.
LICENSE	Controlled-use notice; not a blanket open-source license.

Citation

@dataset{gridexis_assistant_dialogue_pairs_13k_2026,
  title = {Assistant Dialogue Pairs 13K — English Two-Turn Conversations},
  author = {Gridexis},
  year = {2026},
  version = {0.1.0-rc1},
  url = {https://huggingface.co/datasets/Gridexis/assistant-dialogue-pairs-13k}
}

References