Triple
T6769557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Гостиный двор |
E155008
|
entity |
| Predicate | hasTransferCorridorLength |
P17536
|
FINISHED |
| Object | примерно 100 м |
—
|
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: примерно 100 м | Statement: [Гостиный двор, hasTransferCorridorLength, примерно 100 м]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransferCorridorLength Context triple: [Гостиный двор, hasTransferCorridorLength, примерно 100 м]
-
A.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
B.
hasTunnelLengthApprox
Indicates that an entity has a tunnel whose length is approximately a specified value.
-
C.
lengthOfCorridors
chosen
Indicates the measured extent or distance of corridors within a given space or structure.
-
D.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
E.
hasParallelTransit
Indicates that one transit route, service, or segment runs in parallel to another along a similar path or corridor.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d232d1f08190bc30c0f24f28c475 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.