Triple
T12665206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsvetnoy Bulvar |
E302532
|
entity |
| Predicate | hasStationCodeScheme |
P57418
|
FINISHED |
| Object | Moscow Metro numerical code system |
—
|
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: Moscow Metro numerical code system | Statement: [Tsvetnoy Bulvar, hasStationCodeScheme, Moscow Metro numerical code system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationCodeScheme Context triple: [Tsvetnoy Bulvar, hasStationCodeScheme, Moscow Metro numerical code system]
-
A.
hasStationCodeSystem
chosen
Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
-
B.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
C.
hasStationCodeInternal
Indicates that an entity is associated with a specific internal station code used within a system or organization.
-
D.
hasStationCodePrefix
Indicates that one entity’s station code begins with the prefix specified by the other entity.
-
E.
hasCodeScheme
Indicates that something is associated with or organized according to a particular coding or classification scheme.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617e030881908444743b8a7e0d75 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:19 p.m.