Triple
T8531846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maronite Catholic Eparchy of Baalbek-Deir El Ahmar |
E201969
|
entity |
| Predicate | hasClericalCategory |
P3092
|
FINISHED |
| Object | secular clergy |
—
|
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 clergy | Statement: [Maronite Catholic Eparchy of Baalbek-Deir El Ahmar, hasClericalCategory, secular clergy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClericalCategory Context triple: [Maronite Catholic Eparchy of Baalbek-Deir El Ahmar, hasClericalCategory, secular clergy]
-
A.
hasClericalFunction
Indicates that an entity performs, is responsible for, or is associated with a clerical or administrative function.
-
B.
hasClergyType
chosen
Indicates the specific category or role of clergy associated with an entity.
-
C.
hasClericalDiscipline
Indicates that an entity is subject to, or governed by, a particular set of clerical or religious disciplinary rules or practices.
-
D.
isClericIn
Indicates that an entity serves or functions as a cleric within a specified organization, location, or group.
-
E.
hasLiturgicalCategory
Indicates that something is classified under a particular liturgical category within a religious or worship-related system.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe676e2ac8190b65a3d2a935776fd |
completed | March 31, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:17 p.m.