Triple
T33439561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian apparitions of 1877 |
E856322
|
entity |
| Predicate | hasNumberOfApparitions |
P196879
|
FINISHED |
| Object | over 160 |
—
|
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: over 160 | Statement: [Marian apparitions of 1877, hasNumberOfApparitions, over 160]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfApparitions Context triple: [Marian apparitions of 1877, hasNumberOfApparitions, over 160]
-
A.
hasNotableMultipleAppearances
Indicates that an entity appears multiple times in a context or medium in a way considered significant or noteworthy.
-
B.
appearedAt
Indicates that an entity was present or made an appearance at a specific event, location, or occasion.
-
C.
appearedWith
Indicates that two entities were present or participated together in the same context, event, or medium.
-
D.
testAppearances
Indicates that one entity conducts or is involved in tests or experiments concerning the appearances or visual characteristics of another entity.
-
E.
appearsFor
Indicates that one entity is presented, shown, or made visible on behalf of, or in representation of, another entity.
- F. None of above. chosen
Provenance (4 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_69fe6c811bcc81908b1e1b1f8bcb071b |
completed | May 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69fe6c026d5481908b7a814dcf38c183 |
completed | May 8, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fe6c7fc4388190aa88993d00872d7f |
completed | May 8, 2026, 11:06 p.m. |
Created at: May 1, 2026, 1:37 a.m.