Triple
T37650233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCC-VD |
E937152
|
entity |
| Predicate | associatedStationNameCyrillic |
P41163
|
FINISHED |
| Object | Владыкино |
—
|
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: Владыкино | Statement: [MCC-VD, associatedStationNameCyrillic, Владыкино]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStationNameCyrillic Context triple: [MCC-VD, associatedStationNameCyrillic, Владыкино]
-
A.
associatedStation
Indicates a relationship where one entity is linked or connected to a particular station as its relevant or related station.
-
B.
associatedWithStationName
chosen
Indicates a relationship where something is linked or connected to a particular station identified by its name.
-
C.
associatedStationCountry
Indicates that there is a relationship linking a station to the country with which it is associated.
-
D.
associatedStationQualifier
Indicates that a station is linked to another station with a specific qualifying role or context (such as type, function, or relationship).
-
E.
adjacentStationOnKaluzhsko–RizhskayaLine
Indicates that one station is directly next to another station along the Kaluzhsko–Rizhskaya metro line.
- 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_69f76ed4fe908190b8061c5c135e0971 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.