Triple
T31595365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eparchy of Lungro |
E806203
|
entity |
| Predicate | hasClergyOfType |
P3092
|
FINISHED |
| Object | Married priests (according to Eastern discipline) |
—
|
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: Married priests (according to Eastern discipline) | Statement: [Eparchy of Lungro, hasClergyOfType, Married priests (according to Eastern discipline)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClergyOfType Context triple: [Eparchy of Lungro, hasClergyOfType, Married priests (according to Eastern discipline)]
-
A.
hasClergyType
chosen
Indicates the specific category or role of clergy associated with an entity.
-
B.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
-
C.
hasClergyCharacter
Indicates that an entity possesses a religious or clerical role, status, or character.
-
D.
hasClergyOrder
Indicates that an entity is associated with, or belongs to, a specific religious or clerical order.
-
E.
hasClergyLikeGroup
Indicates that an entity possesses or is associated with a group functioning in a clergy-like or religious-leadership role.
- 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_69f348d4891c8190b02bae3c8ecb68b7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: April 30, 2026, 10:30 p.m.