Triple
T30430093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Mariano Jiménez |
E774136
|
entity |
| Predicate | typeOfPriest |
P70093
|
FINISHED |
| Object | secular priest |
—
|
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: secular priest | Statement: [José Mariano Jiménez, typeOfPriest, secular priest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPriest Context triple: [José Mariano Jiménez, typeOfPriest, secular priest]
-
A.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
B.
religiousFigureType
chosen
Indicates the specific role or category of a person recognized as a religious figure (e.g., priest, monk, prophet) within a religious context.
-
C.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
D.
typeOfDeity
Indicates that one entity is classified as a specific kind or category of deity in relation to another.
-
E.
typeOfMonk
Indicates that one entity is a specific kind or category of monk in relation to 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_69f22492d2a88190995ce8745d9becaa |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff6074bcd4819090b72cd6209ff206 |
completed | May 9, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69ff600aba888190812a6e7eca0283b8 |
completed | May 9, 2026, 4:25 p.m. |
Created at: April 29, 2026, 8:06 p.m.