Triple
T138866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood/Vine station |
E2807
|
entity |
| Predicate | ticketBarrierType |
P1740
|
FINISHED |
| Object | turnstiles |
—
|
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: turnstiles | Statement: [Hollywood/Vine station, ticketBarrierType, turnstiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketBarrierType Context triple: [Hollywood/Vine station, ticketBarrierType, turnstiles]
-
A.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
fareControl
chosen
Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
-
C.
admissionFee
Indicates the monetary charge required for entry or participation in a place, event, or activity.
-
D.
barAdmission
Indicates that a legal professional has been formally admitted to practice law before a particular bar or court.
-
E.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a800148190be119d1d075869b8 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.