Triple
T12821277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Value Alliance |
E306534
|
entity |
| Predicate | fareStrategy |
P49336
|
FINISHED |
| Object | low fares with optional add-on services |
—
|
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: low fares with optional add-on services | Statement: [Value Alliance, fareStrategy, low fares with optional add-on services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareStrategy Context triple: [Value Alliance, fareStrategy, low fares with optional add-on services]
-
A.
farePolicyType
Indicates the type or category of fare policy that governs how prices, rules, or conditions are applied.
-
B.
fareModel
Indicates a pricing relationship where a specific fare structure, rule set, or calculation method is applied to determine the cost of a trip or service.
-
C.
fareStructure
Indicates the pricing scheme or set of rules that determine how fares are calculated and applied for a given service or trip.
-
D.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
-
E.
fareStructureFeature
chosen
Indicates a characteristic or condition of how fares are structured, calculated, or applied within a pricing or ticketing system.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9fcc8c8190a926ab0481d28f14 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d964100f7481909a197396003d4a71 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.