Triple
T2490843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novoslobodskaya |
E52035
|
entity |
| Predicate | ticketHallType |
P27344
|
FINISHED |
| Object | subsurface vestibule |
—
|
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: subsurface vestibule | Statement: [Novoslobodskaya, ticketHallType, subsurface vestibule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketHallType Context triple: [Novoslobodskaya, ticketHallType, subsurface vestibule]
-
A.
hasTicketHall
chosen
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
-
B.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
-
C.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
D.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
-
E.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd18fe32081909580c6272a6013c5 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.