Triple
T33439551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian apparitions of 1877 |
E856322
|
entity |
| Predicate | hasNumberOfVisionaries |
P21317
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Marian apparitions of 1877, hasNumberOfVisionaries, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfVisionaries Context triple: [Marian apparitions of 1877, hasNumberOfVisionaries, 2]
-
A.
numberOfVisionaries
chosen
Indicates the quantity or count of entities classified as visionaries in a given context.
-
B.
hasVisionary
Indicates that an entity is associated with or guided by a visionary individual or visionary concept.
-
C.
hasMainVisionary
Indicates that one entity serves as the primary creative or strategic visionary responsible for guiding or shaping another entity.
-
D.
hasVisionaryType
Indicates that an entity is associated with or classified under a particular type or category of visionary.
-
E.
numberOfVisions
Indicates the quantity of visions experienced or associated with an 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
Created at: May 1, 2026, 1:37 a.m.