Triple
T10186314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London fare zone 4 |
E236917
|
entity |
| Predicate | usedForTicketType |
P92594
|
FINISHED |
| Object | single 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: single fares | Statement: [London fare zone 4, usedForTicketType, single fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForTicketType Context triple: [London fare zone 4, usedForTicketType, single fares]
-
A.
usesTicketValidatorType
Indicates that an entity employs or is associated with a specific type or category of ticket validation device or method.
-
B.
usedInE-tickets
Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
-
C.
companionTicketType
Indicates the type or category of ticket that is associated with or issued to a companion of a primary ticket holder.
-
D.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
-
E.
liftTicketType
Indicates the type or category of lift ticket associated with or assigned to an 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded790b488190b1ed4645554873cd |
completed | April 2, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:12 p.m.