Triple
T5002240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mileage Plan |
E112400
|
entity |
| Predicate | accrualType |
P45051
|
FINISHED |
| Object | distance-based earning |
—
|
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: distance-based earning | Statement: [Mileage Plan, accrualType, distance-based earning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accrualType Context triple: [Mileage Plan, accrualType, distance-based earning]
-
A.
accrualMethod
chosen
Indicates the method or basis by which something (such as interest, revenue, or benefits) is accumulated or recognized over time.
-
B.
accessionType
Indicates the manner or category by which something is acquired, added, or admitted into a collection, system, or status.
-
C.
calculationType
Indicates the specific method, formula, or approach used to perform a calculation in the described relationship.
-
D.
billType
Indicates the classification or category assigned to a bill (such as its kind, purpose, or procedural type).
-
E.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.