Triple
T8726042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralteyskaya metro station |
E207132
|
entity |
| Predicate | hasMobileCoverage |
P46630
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Admiralteyskaya metro station, hasMobileCoverage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMobileCoverage Context triple: [Admiralteyskaya metro station, hasMobileCoverage, yes]
-
A.
hasCellService
chosen
Indicates that a location, device, or area is within range of a cellular network and can access mobile phone or data services.
-
B.
hasCellularComponent
Indicates that an entity possesses, includes, or is associated with a specific cellular component as part of its structure or organization.
-
C.
allowsMobileReception
Indicates that one entity provides the conditions or infrastructure necessary for another entity to receive mobile (cellular) network service.
-
D.
networkCoverage
Indicates the extent to which a network’s signal or service is available across a given area or to specific entities.
-
E.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d158b0481908249610458f97306 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:36 p.m.