Triple
T32389679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Белая Троицкая церковь |
E827634
|
entity |
| Predicate | тип сооружения |
P110176
|
FINISHED |
| Object | церковь |
—
|
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: церковь | Statement: [Белая Троицкая церковь, тип сооружения, церковь]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: тип сооружения Context triple: [Белая Троицкая церковь, тип сооружения, церковь]
-
A.
типСтроения
Indicates the specific kind or category of building or structure associated with an entity.
-
B.
constructionType
Indicates the specific method or style by which something is built or constructed.
-
C.
builtInfrastructureType
chosen
Indicates the specific kind or category of built infrastructure associated with or characterized by the subject.
-
D.
buildingStructure
Indicates that one entity is a structural component or physical part that forms, supports, or constitutes the construction of another entity.
-
E.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
- 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_69f349184e7481909c6c54428cb9cf12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1d48d048190b6bb79e26881adb7 |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:52 a.m.