Triple
T12066666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulitsa Gorchakova |
E287312
|
entity |
| Predicate | hasPassengerSystem |
P21784
|
FINISHED |
| Object | contactless payment accepted |
—
|
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 payment accepted | Statement: [Ulitsa Gorchakova, hasPassengerSystem, contactless payment accepted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerSystem Context triple: [Ulitsa Gorchakova, hasPassengerSystem, contactless payment accepted]
-
A.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
-
B.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
C.
hasOnboardSystems
chosen
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
-
D.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
E.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.