Triple
T15333214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sedgwick |
E366592
|
entity |
| Predicate | ticketingMediumAccepted |
P42387
|
FINISHED |
| Object | contactless bankcards |
—
|
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: contactless bankcards | Statement: [Sedgwick, ticketingMediumAccepted, contactless bankcards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingMediumAccepted Context triple: [Sedgwick, ticketingMediumAccepted, contactless bankcards]
-
A.
ticketTypeAccepted
Indicates that a particular type of ticket is valid for use or accepted in a given context or by a given entity.
-
B.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
C.
ticketingScope
Indicates the range or domain within which ticketing actions (such as creation, assignment, or management of tickets) are valid or applicable.
-
D.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
E.
ticketMediumType
chosen
Indicates the type or format of the medium through which a ticket is issued, stored, or presented (e.g., paper, mobile, electronic).
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.