Triple
T26116403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etihad Guest Miles |
E658834
|
entity |
| Predicate | earningRateDependsOn |
P159967
|
FINISHED |
| Object | fare class |
—
|
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: fare class | Statement: [Etihad Guest Miles, earningRateDependsOn, fare class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earningRateDependsOn Context triple: [Etihad Guest Miles, earningRateDependsOn, fare class]
-
A.
earnOn
Indicates that one entity gains income, profit, or returns as a result of another entity or activity.
-
B.
learningCurve
Indicates how the difficulty or required effort to acquire proficiency in a task or system changes as experience or practice increases.
-
C.
regulatesTrainingAccordingTo
Indicates that one entity sets or enforces rules, standards, or guidelines governing how training is conducted in relation to another entity or context.
-
D.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
E.
interestRateDetermination
Indicates the relationship by which the applicable interest rate is set, defined, or adjusted for a financial obligation or instrument.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60ac86d908190bf582de7891fb4b3 |
completed | May 2, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 8:05 p.m.