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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
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.
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