Triple
T17213108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SWA |
E417779
|
entity |
| Predicate | ticketCodeRole |
P126422
|
FINISHED |
| Object | origin station code |
—
|
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: origin station code | Statement: [SWA, ticketCodeRole, origin station code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketCodeRole Context triple: [SWA, ticketCodeRole, origin station code]
-
A.
ticketDesignatorRole
Indicates the specific role or function associated with a ticket designator within a ticketing or fare context.
-
B.
ticketingCode
Indicates the specific fare or booking code associated with a ticket that defines its pricing, rules, and conditions of use.
-
C.
ticketTypeStored
Indicates that a particular type of ticket has been recorded and saved in a storage or system.
-
D.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
-
E.
ticketOfTarget
Indicates that one entity is a ticket associated with, or issued for, a specific target entity.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dc795d08190b90801a4f8b23afe |
completed | April 19, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:38 a.m.