Triple
T6909148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mystery of the Church |
E159886
|
entity |
| Predicate | treatsConcept |
P531
|
FINISHED |
| Object | Church as People of God |
—
|
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: Church as People of God | Statement: [The Mystery of the Church, treatsConcept, Church as People of God]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsConcept Context triple: [The Mystery of the Church, treatsConcept, Church as People of God]
-
A.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
B.
hasConcept
chosen
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
C.
protectedConcept
Indicates that one entity is a concept or attribute that is legally or normatively safeguarded from discrimination, harm, or unauthorized use in relation to another entity.
-
D.
treatment
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
E.
categoryConcept
Indicates that one entity serves as a categorical type or conceptual class under which the other entity is grouped or classified.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9be98748190b5cb698e66e3aa42 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.