Triple
T32983210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frunzenskaya metro station |
E843861
|
entity |
| Predicate | numberOfEscalatorBanks |
P103914
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Frunzenskaya metro station, numberOfEscalatorBanks, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEscalatorBanks Context triple: [Frunzenskaya metro station, numberOfEscalatorBanks, 1]
-
A.
hasNumberOfElevatorBanks
Indicates the relationship specifying how many distinct elevator banks are present in or associated with a given entity.
-
B.
numberOfEscalators
chosen
Indicates the quantity of escalators associated with or present in a given entity or location.
-
C.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
D.
numberOfElevators
Indicates the total count of elevators associated with a given entity or location.
-
E.
hasEscalatorDepthRank
Indicates the relative position or level of an escalator within an ordered hierarchy of escalators (e.g., by depth, floor, or sequence).
- 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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0226c8b2f881909de3c1a5ba40fc49 |
completed | May 11, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_6a0225602acc8190978ab4aacc615b8d |
completed | May 11, 2026, 6:52 p.m. |
Created at: May 1, 2026, 1:22 a.m.