Triple
T6054030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacinta Marto |
E134862
|
entity |
| Predicate | childAgeDuringApparitions |
P40603
|
FINISHED |
| Object | 7 years old |
—
|
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: 7 years old | Statement: [Jacinta Marto, childAgeDuringApparitions, 7 years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childAgeDuringApparitions Context triple: [Jacinta Marto, childAgeDuringApparitions, 7 years old]
-
A.
apparitionsDate
Indicates the date on which the apparitions are reported or believed to have occurred.
-
B.
childInMyth
Indicates that one entity is described or portrayed as the child (offspring) of another entity within a mythological or legendary context.
-
C.
victimAge
Indicates the age of the person who is the victim in the described event or situation.
-
D.
reportedApparitionEntity
Indicates that an entity has been reported or described as an apparition in some account or observation.
-
E.
visionaryAgeAtFirstApparition
chosen
Indicates the age of the visionary at the time of their first reported apparition.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05708fda48190ad3d1860969ebb6a |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:09 p.m.