Triple
T2634416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travelcard |
E59709
|
entity |
| Predicate | ticketMediumType |
P42387
|
FINISHED |
| Object | magnetic stripe paper |
—
|
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: magnetic stripe paper | Statement: [Travelcard, ticketMediumType, magnetic stripe paper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketMediumType Context triple: [Travelcard, ticketMediumType, magnetic stripe paper]
-
A.
ticket
Indicates that an entity serves as or is associated with a ticket, typically representing authorization, access, or a record for an event, service, or transaction.
-
B.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
C.
ticketingProduct
Indicates a relationship where an entity is associated with, or offered as, a ticketing-related product (such as a service or item used for issuing, managing, or selling tickets).
-
D.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
-
E.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e085b0819089db4103c0d8cd9b |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8abcc348190bfa05c0abc4bcee7 |
completed | March 7, 2026, 7:50 a.m. |
Created at: March 6, 2026, 9:50 p.m.