Triple
T13889438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPS-1 |
E333930
|
entity |
| Predicate | salaryCharacteristic |
P56782
|
FINISHED |
| Object | minimum basic salary in BPS system |
—
|
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: minimum basic salary in BPS system | Statement: [BPS-1, salaryCharacteristic, minimum basic salary in BPS system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: salaryCharacteristic Context triple: [BPS-1, salaryCharacteristic, minimum basic salary in BPS system]
-
A.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
-
B.
payScale
chosen
Indicates the compensation level or salary range assigned to an entity, typically reflecting its relative pay or grade within a structured system.
-
C.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
D.
salaryMilestone
Indicates a specific salary-related threshold or achievement that has been reached or is being targeted in relation to an entity.
-
E.
careerEarningsApprox
Indicates an approximate total amount of money an entity has earned over the course of its career.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a3a24881908d81d634622fbbcc |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.