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README.md
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- name: time
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dtype: string
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- name: tz_offset_hours
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dtype: float64
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- name: place
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dtype: string
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- name: lat
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dtype: float64
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- name: lon
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dtype: float64
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- name: zodiac_type
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dtype: string
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- name: ascendant
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- name: longitude
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dtype: float64
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- name: rashi
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dtype: int64
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dtype: string
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- name: Moon
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dtype: float64
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dtype: string
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- name: Mars
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- name: longitude
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: string
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dtype: string
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dtype: int64
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dtype: string
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dtype: float64
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dtype: float64
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dtype: string
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list:
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dtype: string
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list:
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dtype: string
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- name: user_question
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dtype: string
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- name: response
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dtype: string
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- name: citations
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list: string
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- name: source
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dtype: string
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splits:
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- name: train
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num_bytes: 243487015
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num_examples: 89916
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- name: validation
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num_bytes: 13734267
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num_examples: 5104
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- name: test
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num_bytes: 13424054
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num_examples: 4980
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download_size: 185423310
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dataset_size: 270645336
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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- split: test
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path: data/test-*
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---
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| 1 |
---
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+
license: apache-2.0
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+
task_categories:
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- text-generation
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language:
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- en
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tags:
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- astrology
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- kp-astrology
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- krishnamurti-paddhati
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- vedic-astrology
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- sub-lord
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+
pretty_name: KP System (Krishnamurti Paddhati) SFT Dataset
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+
size_categories:
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- 100K<n<1M
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| 16 |
---
|
| 17 |
+
|
| 18 |
+
# KP System (Krishnamurti Paddhati) SFT Dataset
|
| 19 |
+
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+
Sidereal Vedic chart plus KP's distinguishing sub-lord layer — each planet and the Ascendant get a sub-lord via proportional nakshatra subdivision.
|
| 21 |
+
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+
| | |
|
| 23 |
+
|---|---|
|
| 24 |
+
| Total examples | 100000 |
|
| 25 |
+
| Train / Validation / Test | 89916 / 5104 / 4980 |
|
| 26 |
+
| Question types | 4 |
|
| 27 |
+
| Avg citations per example | 4.097 |
|
| 28 |
+
| Zero-citation examples | 0 |
|
| 29 |
+
|
| 30 |
+
## Computation
|
| 31 |
+
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| 32 |
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Deterministic astronomy (pyswisseph, Lahiri sidereal) + a proportional-subdivision sub-lord formula.
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| 33 |
+
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+
## Validation status — read before trusting this at scale
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| 35 |
+
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+
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).
|
| 37 |
+
|
| 38 |
+
## Schema
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| 39 |
+
|
| 40 |
+
| Field | Type | Description |
|
| 41 |
+
|---|---|---|
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| 42 |
+
| `example_id` | string | `{synthetic_id}_{question_type}` |
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| 43 |
+
| `synthetic_id` | string | ID of the underlying synthetic input |
|
| 44 |
+
| `system` | string | `"kp_system"` |
|
| 45 |
+
| `facts` | dict | Full computed output for this system (chart/pillars/numbers depending on system) |
|
| 46 |
+
| `retrieved_rules` | list[dict] | Rules/observations matched for this input |
|
| 47 |
+
| `question_type` | string | See distribution below |
|
| 48 |
+
| `user_question` | string | Synthetic user question |
|
| 49 |
+
| `response` | string | Grounded reading — every claim traces to `facts` or `retrieved_rules` |
|
| 50 |
+
| `citations` | list[string] | Which rules the response draws on |
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| 51 |
+
| `source` | string | `"rule_matched"` for all rows in this version |
|
| 52 |
+
|
| 53 |
+
Question type distribution: `general_natal`: 25000, `career`: 25000, `marriage_timing`: 25000, `sub_lord_reading`: 25000
|
| 54 |
+
|
| 55 |
+
## Usage
|
| 56 |
+
|
| 57 |
+
```python
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| 58 |
+
from datasets import load_dataset
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| 59 |
+
|
| 60 |
+
ds = load_dataset("YOUR_USERNAME/kp_system-sft")
|
| 61 |
+
print(ds)
|
| 62 |
+
|
| 63 |
+
ex = ds["train"][0]
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| 64 |
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print(ex["user_question"])
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| 65 |
+
print(ex["response"])
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| 66 |
+
```
|
| 67 |
+
|
| 68 |
+
## What this dataset does NOT claim
|
| 69 |
+
|
| 70 |
+
Like every dataset in this collection, this teaches a model to narrate a
|
| 71 |
+
correctly-computed KP System (Krishnamurti Paddhati) reading using its own traditional rules
|
| 72 |
+
faithfully and with citations. It does not, and cannot, contain any
|
| 73 |
+
ground truth about whether any prediction comes true — no such data
|
| 74 |
+
exists for any divination system. See the companion repo's top-level
|
| 75 |
+
README for the shared "what these datasets don't claim" statement that
|
| 76 |
+
applies across the whole collection.
|
| 77 |
+
|
| 78 |
+
## Known limitations
|
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- Uses Lahiri ayanamsa, not the KP (Krishnamurti) ayanamsa some strict KP practitioners prefer — a documented simplification, not a KP-specific correction.
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- Only 1 level of sub-lord is computed (not the further sub-sub-lord some KP practice uses).
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- 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.
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## Companion repo
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Full generation pipeline (8 systems, shared scripts) — for regenerating
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at larger scale or extending the rule set — is the companion GitHub repo
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`astrology-datasets` (update this link once pushed).
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## License
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Apache 2.0. All computed data is synthetic (no real people). Rule/effect
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text is written in-house, paraphrasing widely known traditional
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principles, not reproduced from any single copyrighted source.
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