Triple
T1339518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gostiny Dvor metro station |
E28432
|
entity |
| Predicate | transferType |
P27343
|
FINISHED |
| Object | cross-platform transfer via passageways |
—
|
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: cross-platform transfer via passageways | Statement: [Gostiny Dvor metro station, transferType, cross-platform transfer via passageways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transferType Context triple: [Gostiny Dvor metro station, transferType, cross-platform transfer via passageways]
-
A.
hasTransfer
Indicates a relationship where something is moved or conveyed from one entity or location to another.
-
B.
functionTransferredTo
Indicates that a specific function, role, or responsibility has been moved from one entity to another.
-
C.
capitalMovedFrom
Indicates that a capital city was relocated from one place (the source) to another (the destination).
-
D.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
-
E.
transferFunctionType
Indicates the specific kind or category of transfer function that characterizes how input signals are transformed into output signals in a system.
- F. None of above. chosen
Provenance (4 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c21303c881908fef0b32831222fe |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef3e8fc8190ac9a1ba9b5879483 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:56 p.m.