Triple
T5739176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Governments of India |
E126571
|
entity |
| Predicate | numberOfConstituentUnits |
P19248
|
FINISHED |
| Object | 28 |
—
|
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: 28 | Statement: [State Governments of India, numberOfConstituentUnits, 28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConstituentUnits Context triple: [State Governments of India, numberOfConstituentUnits, 28]
-
A.
numberOfConstituents
Indicates the total count of individual components or members that make up a larger whole or group.
-
B.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
C.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
D.
constitutedBy
Indicates that something is made up of, composed from, or formed by the specified parts or elements.
-
E.
minorUnitsPerUnit
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255dc35c8190ab9ee5d269ce553a |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.