Triple
T14061379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | subah (Mughal provincial administration) |
E338353
|
entity |
| Predicate | hasRevenueSystem |
P112669
|
FINISHED |
| Object | zabt system in many regions |
—
|
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: zabt system in many regions | Statement: [subah (Mughal provincial administration), hasRevenueSystem, zabt system in many regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRevenueSystem Context triple: [subah (Mughal provincial administration), hasRevenueSystem, zabt system in many regions]
-
A.
hasRevenueUnit
Indicates that an entity’s revenue is measured, reported, or associated in terms of a specified unit (e.g., currency or measurement unit).
-
B.
usesRevenueModel
Indicates that one entity applies or operates according to a particular revenue model to generate income.
-
C.
hasBroadcastRevenueModel
Indicates that one entity uses or is associated with a particular revenue model based on broadcasting activities.
-
D.
hasReservationSystem
Indicates that an entity uses or is equipped with a system for managing reservations or bookings.
-
E.
enteredRevenueService
Indicates that an entity has begun working for or joined the revenue (tax) service organization.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568876308190840361dcaf10bd45 |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:21 p.m.