Triple
T8141802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medallion Qualification Miles |
E190114
|
entity |
| Predicate | accrualDependsOn |
P19751
|
FINISHED |
| Object | ticketing carrier |
—
|
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: ticketing carrier | Statement: [Medallion Qualification Miles, accrualDependsOn, ticketing carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accrualDependsOn Context triple: [Medallion Qualification Miles, accrualDependsOn, ticketing carrier]
-
A.
accrualUnit
Indicates the unit of measure (such as days, months, or years) in which something accumulates or is accrued over time.
-
B.
accrualMethod
Indicates the method or basis by which something (such as interest, revenue, or benefits) is accumulated or recognized over time.
-
C.
contingentOn
chosen
Indicates that the occurrence, validity, or outcome of one event or condition depends on the fulfillment or existence of another.
-
D.
conceptuallyDependsOn
Indicates that one entity’s definition, validity, or understanding relies on or is grounded in the concepts provided by another entity.
-
E.
durationDependsOn
Indicates that the length of time of one event or state is determined or influenced by another event, condition, or factor.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4442299881909db56f7475cbb99a |
completed | March 31, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:36 p.m.