Triple
T35384553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kruhlouniversytetska Street |
E1022749
|
entity |
| Predicate | hasNearbyMetroSystem |
P33877
|
FINISHED |
| Object | Kyiv Metro |
—
|
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: Kyiv Metro | Statement: [Kruhlouniversytetska Street, hasNearbyMetroSystem, Kyiv Metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMetroSystem Context triple: [Kruhlouniversytetska Street, hasNearbyMetroSystem, Kyiv Metro]
-
A.
hasNearbyOvergroundLine
Indicates that one entity is located close to an above-ground railway or transit line associated with the other entity.
-
B.
nearestMajorMetro
Indicates the relationship where a given location is associated with the closest large metropolitan area to it.
-
C.
hasNearbyUndergroundStationEntrance
Indicates that one entity is located close to an entrance of an underground (subway/metro) station.
-
D.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
E.
nearMetroStation
chosen
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00119d821c8190874786391b27ef23 |
completed | May 10, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_6a001143fb6881909ac0ae8bfea04351 |
completed | May 10, 2026, 5:01 a.m. |
Created at: May 3, 2026, 4:03 p.m.