Triple
T37340166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabaty |
E927011
|
entity |
| Predicate | hasTransportTerminus |
P1297
|
FINISHED |
| Object | Kabaty metro station |
—
|
NE NERFINISHED |
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: Kabaty metro station | Statement: [Kabaty, hasTransportTerminus, Kabaty metro station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportTerminus Context triple: [Kabaty, hasTransportTerminus, Kabaty metro station]
-
A.
hasBusTerminalType
Indicates the specific category or type of bus terminal associated with an entity.
-
B.
hasPassengerTerminal
chosen
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
C.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
D.
hasTransportHub
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
-
E.
hasPassengerTerminalSection
Indicates that something includes or is associated with a specific section or subdivision of a passenger terminal.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a001cc0ff588190bb7c8a6fd427d02b |
completed | May 10, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_6a001b3ea18c8190aeda7a32b2697490 |
completed | May 10, 2026, 5:44 a.m. |
Created at: May 3, 2026, 4:16 p.m.