---
license: apache-2.0
task_categories:
  - text-generation
language:
  - en
tags:
  - astrology
  - kp-astrology
  - krishnamurti-paddhati
  - vedic-astrology
  - sub-lord
pretty_name: KP System (Krishnamurti Paddhati) SFT Dataset
size_categories:
  - 100K<n<1M
---

# KP System (Krishnamurti Paddhati) SFT Dataset

Sidereal Vedic chart plus KP's distinguishing sub-lord layer — each planet and the Ascendant get a sub-lord via proportional nakshatra subdivision.

| | |
|---|---|
| Total examples | 100000 |
| Train / Validation / Test | 89916 / 5104 / 4980 |
| Question types | 4 |
| Avg citations per example | 4.097 |
| Zero-citation examples | 0 |

## Computation

Deterministic astronomy (pyswisseph, Lahiri sidereal) + a proportional-subdivision sub-lord formula.

## Validation status — read before trusting this at scale

Sub-lord formula independently checked for internal consistency: the 9 proportional spans sum to exactly one nakshatra (13°20') with no gaps or overlaps, and produce exactly the 9 expected lords in the correct sequence across a fine-grained scan (see companion repo tests/test_kp_sublord.py).

## Schema

| Field | Type | Description |
|---|---|---|
| `example_id` | string | `{synthetic_id}_{question_type}` |
| `synthetic_id` | string | ID of the underlying synthetic input |
| `system` | string | `"kp_system"` |
| `facts` | dict | Full computed output for this system (chart/pillars/numbers depending on system) |
| `retrieved_rules` | list[dict] | Rules/observations matched for this input |
| `question_type` | string | See distribution below |
| `user_question` | string | Synthetic user question |
| `response` | string | Grounded reading — every claim traces to `facts` or `retrieved_rules` |
| `citations` | list[string] | Which rules the response draws on |
| `source` | string | `"rule_matched"` for all rows in this version |

Question type distribution: `general_natal`: 25000, `career`: 25000, `marriage_timing`: 25000, `sub_lord_reading`: 25000

## Usage

```python
from datasets import load_dataset

ds = load_dataset("YOUR_USERNAME/kp_system-sft")
print(ds)

ex = ds["train"][0]
print(ex["user_question"])
print(ex["response"])
```

## What this dataset does NOT claim

Like every dataset in this collection, this teaches a model to narrate a
correctly-computed KP System (Krishnamurti Paddhati) reading using its own traditional rules
faithfully and with citations. It does not, and cannot, contain any
ground truth about whether any prediction comes true — no such data
exists for any divination system. See the companion repo's top-level
README for the shared "what these datasets don't claim" statement that
applies across the whole collection.

## Known limitations

- Uses Lahiri ayanamsa, not the KP (Krishnamurti) ayanamsa some strict KP practitioners prefer — a documented simplification, not a KP-specific correction.
- Only 1 level of sub-lord is computed (not the further sub-sub-lord some KP practice uses).
- No house-cusp sub-lords (KP's horary/timing technique often works from cusp sub-lords, not just planet sub-lords) — only planet and Ascendant sub-lords in this version.

## Companion repo

Full generation pipeline (8 systems, shared scripts) — for regenerating
at larger scale or extending the rule set — is the companion GitHub repo
`astrology-datasets` (update this link once pushed).

## License

Apache 2.0. All computed data is synthetic (no real people). Rule/effect
text is written in-house, paraphrasing widely known traditional
principles, not reproduced from any single copyrighted source.