Triple
T10443633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warszawska Karta Miejska |
E246229
|
entity |
| Predicate | ticketTypeStored |
P94059
|
FINISHED |
| Object | time tickets |
—
|
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: time tickets | Statement: [Warszawska Karta Miejska, ticketTypeStored, time tickets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketTypeStored Context triple: [Warszawska Karta Miejska, ticketTypeStored, time tickets]
-
A.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
-
B.
ticketFormat
Indicates the specific structure, layout, or template in which a ticket is represented or issued.
-
C.
liftTicketType
Indicates the type or category of lift ticket associated with or assigned to an entity.
-
D.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
E.
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.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:15 p.m.