Triple
T36500063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Kuntsevych |
E899298
|
entity |
| Predicate | hasBeatificationDate |
P11002
|
FINISHED |
| Object | 1643 |
—
|
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: 1643 | Statement: [Ivan Kuntsevych, hasBeatificationDate, 1643]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeatificationDate Context triple: [Ivan Kuntsevych, hasBeatificationDate, 1643]
-
A.
beatificationDate
chosen
Indicates the date on which a person was officially declared blessed (beatified) in a religious context.
-
B.
hasCauseOfBeatification
Indicates that one entity is the reason or cause for another entity’s beatification.
-
C.
canonizationDate
Indicates the date on which an individual was officially declared a saint (canonized) by a religious authority.
-
D.
dateOfCanonizationStatus
Indicates the date on which an entity’s canonization status (such as being declared a saint or blessed) was formally conferred or recorded.
-
E.
placeOfBeatification
Indicates the location where a person was formally declared beatified in a religious context.
- 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:10 p.m.