Triple
T26801816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slavyanskaya Square |
E671121
|
entity |
| Predicate | hasNearbyMetroEntrance |
P119624
|
FINISHED |
| Object | Kitay-gorod north vestibule |
—
|
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: Kitay-gorod north vestibule | Statement: [Slavyanskaya Square, hasNearbyMetroEntrance, Kitay-gorod north vestibule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMetroEntrance Context triple: [Slavyanskaya Square, hasNearbyMetroEntrance, Kitay-gorod north vestibule]
-
A.
hasNearbyUndergroundStationEntrance
chosen
Indicates that one entity is located close to an entrance of an underground (subway/metro) station.
-
B.
hasSubwayStationEntrance
Indicates that one entity serves as an entrance or access point to a subway station associated with another entity.
-
C.
nearMetroStation
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
-
D.
nearestMajorMetro
Indicates the relationship where a given location is associated with the closest large metropolitan area to it.
-
E.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
- 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_69eeb31fbd888190a82dac5822e453bc |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 27, 2026, 4:23 a.m.