Triple
T31151185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novokuznetskaya station |
E794075
|
entity |
| Predicate | hasPylonsCladIn |
P171198
|
FINISHED |
| Object | dark grey and white marble |
—
|
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: dark grey and white marble | Statement: [Novokuznetskaya station, hasPylonsCladIn, dark grey and white marble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPylonsCladIn Context triple: [Novokuznetskaya station, hasPylonsCladIn, dark grey and white marble]
-
A.
hasPylonColor
Indicates that an entity (such as a pylon or structure) possesses a specific color as one of its attributes.
-
B.
hasPylon
Indicates that one entity possesses, includes, or is equipped with a pylon as part of its structure or configuration.
-
C.
hasPylonCount
Indicates the relationship specifying how many pylons are associated with or present in a given entity.
-
D.
hasArmorPlating
Indicates that one entity is equipped with or covered by protective armor plating in relation to another entity or context.
-
E.
wearsInsigniaAt
Indicates that an entity is wearing or displaying a particular insignia at a specified location or point in time.
- F. None of above. chosen
Provenance (4 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c6f01e881908fa84f5d429d37ae |
completed | May 3, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f69c2127088190ae92c72461576d3b |
completed | May 3, 2026, 12:51 a.m. |
Created at: April 29, 2026, 9:06 p.m.