---
language:
  - en
license: cc-by-sa-4.0
task_categories:
  - text-retrieval
  - sentence-similarity
task_ids:
  - semantic-similarity-classification
tags:
  - dogs
  - dog-breeds
  - retrieval
  - n-tuple
  - hard-negatives
  - sentence-transformers
  - wikipedia
pretty_name: Dog Breed N-Tuple Retrieval Dataset
size_categories:
  - 1K<n<10K
source_datasets:
  - Wikipedia (en)
---

# Dog Breed N-Tuple Retrieval Dataset

A hard-negative-mined **n-tuple** dataset for training and evaluating
sentence embedding / bi-encoder retrieval models on dog-breed knowledge.

## Dataset construction

1. **Source**: English Wikipedia articles for 60+ dog breeds
   (popular/AKC breeds + recognized Indian breeds).
2. **Sections captured**: Appearance, Temperament, Health, History, Care,
   Characteristics, and article summaries — extracted recursively so nested
   subsections are not missed.
3. **Anchor generation**: Up to 2 paraphrased query templates per passage
   (e.g. *"What is the temperament of the Labrador Retriever?"*).
4. **Hard-negative mining**: FAISS-backed TopK mining with
   `sentence-transformers/all-MiniLM-L6-v2`, NV-Retriever-style
   positive-aware margin (`relative_margin=0.05`), and a **cross-breed
   metadata mask** that forbids negatives from the same breed as the anchor.
5. **Train / eval split**: held out by *breed* (not by row) so the eval
   split measures generalization to unseen breed names.

## Column schema

| Column | Description |
|---|---|
| `anchor` | Natural-language query about a breed |
| `positive` | Wikipedia passage that answers the query |
| `negative_1` … `negative_5` | Hard-negative passages from different breeds |

## Splits

| Split | Rows | Breeds |
|---|---|---|
| train | see dataset | ~85 % of breeds |
| eval  | see dataset | ~15 % of breeds (held out by breed) |

## Usage

```python
from datasets import load_dataset
from sentence_transformers import SentenceTransformer
from sentence_transformers.losses import MultipleNegativesRankingLoss

ds = load_dataset("dorrito-dev/dog-breed-ntuple-retrieval")
train = ds["train"]
```

## License

Derived from Wikipedia content, which is licensed under
[CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).