Triple
T3585418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dmitry Donskoy |
E75896
|
entity |
| Predicate | sainthoodType |
P18301
|
FINISHED |
| Object | local saint of Moscow |
—
|
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: local saint of Moscow | Statement: [Dmitry Donskoy, sainthoodType, local saint of Moscow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sainthoodType Context triple: [Dmitry Donskoy, sainthoodType, local saint of Moscow]
-
A.
typeOfSaint
chosen
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
B.
venerationOfSaints
Indicates the act of showing honor, reverence, or devotional respect toward saints.
-
C.
venerationType
Indicates the specific manner or category of reverence or worship directed toward an entity.
-
D.
sacredStatus
Indicates that something holds a revered, holy, or religiously significant status within a particular belief system or tradition.
-
E.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc135ee3481908ef8dc41af632710 |
completed | March 8, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69adb839b4e08190b1c0d611cccb11ae |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.