Triple
T1083397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian philosophical texts (Darśanas) |
E23997
|
entity |
| Predicate | traditionallyDividedInto |
P23759
|
FINISHED |
| Object | āstika schools |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: āstika schools | Statement: [Indian philosophical texts (Darśanas), traditionallyDividedInto, āstika schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionallyDividedInto Context triple: [Indian philosophical texts (Darśanas), traditionallyDividedInto, āstika schools]
-
A.
historicallyDividedInto
Indicates that an entity was separated into multiple distinct parts or regions during a past historical period.
-
B.
dividedStatesInto
Indicates that one entity partitioned another entity into multiple distinct states or regions.
-
C.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
-
D.
politicallyDividedInto
Indicates that a political entity is formally separated into distinct internal political units or regions.
-
E.
divisionTitle
Indicates the formal name or title assigned to a specific division within a larger organization or structure.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95e56948190a1e92367ad7240b7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73f4310819086281f8ec67d1a32 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.