Triple
T410498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province IV |
E9478
|
entity |
| Predicate | hasLayParticipation |
P2434
|
FINISHED |
| Object | lay representatives from member dioceses |
—
|
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: lay representatives from member dioceses | Statement: [Province IV, hasLayParticipation, lay representatives from member dioceses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayParticipation Context triple: [Province IV, hasLayParticipation, lay representatives from member dioceses]
-
A.
hasLayMembersCount
Indicates the number of lay (non-clergy or non-professional) members associated with an entity.
-
B.
hasParticipants
chosen
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
C.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
E.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.