Triple
T2623159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pobeda |
E59054
|
entity |
| Predicate | costStructure |
P32811
|
FINISHED |
| Object | unbundled fares |
—
|
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: unbundled fares | Statement: [Pobeda, costStructure, unbundled fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costStructure Context triple: [Pobeda, costStructure, unbundled fares]
-
A.
costModel
Indicates the pricing or cost-structure relationship applied to an entity, defining how its costs are calculated or charged.
-
B.
programCost
Indicates the monetary or resource expenditure required to implement, run, or participate in a particular program.
-
C.
costToUser
Indicates the amount of cost or expense that is borne by, charged to, or incurred by the user.
-
D.
estimatedCost
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
E.
fareStructure
chosen
Indicates the pricing scheme or set of rules that determine how fares are calculated and applied for a given service or trip.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd80f48888190afdf7e3e042157d0 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.