Triple
T15004492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | administration of Akbar |
E377673
|
entity |
| Predicate | revenueAssessmentBasis |
P6447
|
FINISHED |
| Object | average produce of past ten years |
—
|
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: average produce of past ten years | Statement: [administration of Akbar, revenueAssessmentBasis, average produce of past ten years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revenueAssessmentBasis Context triple: [administration of Akbar, revenueAssessmentBasis, average produce of past ten years]
-
A.
revenueAssessedOn
Indicates that a specific amount of revenue has been formally evaluated and assigned to an entity, typically for accounting, reporting, or taxation purposes.
-
B.
calculationBasis
chosen
Indicates the rule, method, or reference standard used as the foundation for performing a calculation in the relationship.
-
C.
taxationMethod
Indicates the specific way or system by which taxes are calculated, collected, or applied in a given context.
-
D.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
E.
assessmentBasis
Indicates the underlying criteria, evidence, or method used as the foundation for making an assessment or evaluation between entities.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7322b5c81909089cbbf816e1436 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.