Triple
T27942428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Владимирская |
E700787
|
entity |
| Predicate | connectedByTransferPassageTo |
P124479
|
FINISHED |
| Object | Dostoyevskaya |
—
|
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: Dostoyevskaya | Statement: [Владимирская, connectedByTransferPassageTo, Dostoyevskaya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectedByTransferPassageTo Context triple: [Владимирская, connectedByTransferPassageTo, Dostoyevskaya]
-
A.
linkedByCorridor
Indicates that two locations are directly connected to each other by a corridor.
-
B.
passagewayConnection
chosen
Indicates a relationship where one passageway provides a direct route or link between two locations or spaces.
-
C.
connectedByPeopleMoverTo
Indicates that two locations are linked by a people mover system that transports people between them.
-
D.
connectedByStraitTo
Indicates that one entity is geographically linked to another by a narrow body of water known as a strait.
-
E.
hasFareGateConnectionTo
Indicates that there is a direct passage or connection between two areas that is controlled or mediated by fare gates.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: April 27, 2026, 7:19 p.m.