Triple
T1044183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathiawar Agency |
E22537
|
entity |
| Predicate | hadSubordinateUnits |
P11471
|
FINISHED |
| Object | princely states |
—
|
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: princely states | Statement: [Kathiawar Agency, hadSubordinateUnits, princely states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSubordinateUnits Context triple: [Kathiawar Agency, hadSubordinateUnits, princely states]
-
A.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
B.
hasSubnationalCounterpart
Indicates that an entity has a corresponding or equivalent entity at a lower (subnational) administrative level.
-
C.
subsidiaryUnit
chosen
Indicates that one organizational unit functions as a subordinate or dependent division of another, higher-level unit.
-
D.
hasSubregionStatus
Indicates that one region holds an official or defined status as a subregion within a larger geographic or administrative area.
-
E.
formerSubunit
Indicates that one entity was previously a subunit or subordinate part of another entity, but no longer holds that status.
- F. None of above.
Provenance (3 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8475ab48190848388eea6448cb6 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.