Triple
T6231013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin ABC |
E139351
|
entity |
| Predicate | ticketTypeExample |
P69646
|
FINISHED |
| Object | single ticket Berlin ABC |
—
|
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 ticket Berlin ABC | Statement: [Berlin ABC, ticketTypeExample, single ticket Berlin ABC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketTypeExample Context triple: [Berlin ABC, ticketTypeExample, single ticket Berlin ABC]
-
A.
ticketFormat
Indicates the specific structure, layout, or template in which a ticket is represented or issued.
-
B.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
C.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
-
D.
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).
-
E.
ticketMediumType
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. 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ec5be4819084d6df2e8dd2a542 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c05707d5408190a1d0fd80414ad957 |
completed | March 22, 2026, 8:54 p.m. |
Created at: March 22, 2026, 4:22 p.m.