Triple
T30161472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LONDON TERMINALS (on tickets) |
E766676
|
entity |
| Predicate | ticketingSystemCodeType |
P112657
|
FINISHED |
| Object | destination group 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: destination group code | Statement: [LONDON TERMINALS (on tickets), ticketingSystemCodeType, destination group code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingSystemCodeType Context triple: [LONDON TERMINALS (on tickets), ticketingSystemCodeType, destination group code]
-
A.
ticketingCode
Indicates the specific fare or booking code associated with a ticket that defines its pricing, rules, and conditions of use.
-
B.
ticketSystemType
chosen
Indicates the type or category of ticketing system associated with an entity or interaction.
-
C.
ticketCodeRole
Indicates a relationship where a specific ticket code is associated with a particular role or permission.
-
D.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
-
E.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
- 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_69f2247a968881909d79c18f2bfcb275 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67edb30d8819097a9f90443428fc2 |
completed | May 2, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:21 p.m.