Triple
T18038706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dubawi |
E431581
|
entity |
| Predicate | earningsApprox |
P55500
|
FINISHED |
| Object | £750000 |
—
|
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: £750000 | Statement: [Dubawi, earningsApprox, £750000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earningsApprox Context triple: [Dubawi, earningsApprox, £750000]
-
A.
careerEarningsApprox
chosen
Indicates an approximate total amount of money an entity has earned over the course of its career.
-
B.
payScale
Indicates the compensation level or salary range assigned to an entity, typically reflecting its relative pay or grade within a structured system.
-
C.
approximateStipend
Indicates an estimated or rough amount of stipend associated with an entity or situation.
-
D.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
E.
canEarnOn
Indicates that an entity is able or permitted to receive or generate earnings from another entity, source, or activity.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3cbe8c8190ba216eeebfc3cbec |
completed | April 19, 2026, 11:36 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.