Triple
T12464391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lutheran Church of Cameroon |
E297883
|
entity |
| Predicate | hasLaityType |
P60083
|
FINISHED |
| Object | baptized members |
—
|
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: baptized members | Statement: [Lutheran Church of Cameroon, hasLaityType, baptized members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaityType Context triple: [Lutheran Church of Cameroon, hasLaityType, baptized members]
-
A.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
B.
hasParishType
Indicates that an entity is associated with or classified by a specific type or category of parish.
-
C.
hasViewOnLaity
Indicates that one entity holds a particular stance, opinion, or doctrinal position regarding the role or nature of laypeople.
-
D.
hasLayOrganizationType
chosen
Indicates that an entity is associated with a specific type or category of lay (non-clerical) organizational structure.
-
E.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.