Triple
T27450072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir Mikhailovich Gundyayev |
E692408
|
entity |
| Predicate | monasticTonsureName |
P50298
|
FINISHED |
| Object | Kirill |
—
|
NE NERFINISHED |
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: Kirill | Statement: [Vladimir Mikhailovich Gundyayev, monasticTonsureName, Kirill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monasticTonsureName Context triple: [Vladimir Mikhailovich Gundyayev, monasticTonsureName, Kirill]
-
A.
monasticTonsure
Indicates the act or state of a person being ritually shaved or having their hair cut as part of entering or belonging to a monastic or religious order.
-
B.
placeOfMonasticTonsure
Indicates the location where a person formally received monastic tonsure (i.e., was ritually admitted into monastic life).
-
C.
hasMonasticName
chosen
Indicates that an entity possesses a specific name adopted or assigned within a monastic or religious order.
-
D.
monasticDress
Indicates that an entity wears or is characterized by clothing associated with a monastic or religious order.
-
E.
typeOfMonk
Indicates that one entity is a specific kind or category of monk in relation to another entity.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62dc4980481909e303ade433c7d61 |
completed | May 2, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 12:47 p.m.