Triple
T19428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholicism |
E384
|
entity |
| Predicate | hasGlobalPresence |
P1381
|
FINISHED |
| Object | worldwide |
—
|
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: worldwide | Statement: [Roman Catholicism, hasGlobalPresence, worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlobalPresence Context triple: [Roman Catholicism, hasGlobalPresence, worldwide]
-
A.
hasGlobalReach
chosen
Indicates that an entity’s influence, operations, or impact extends across multiple countries or worldwide.
-
B.
hasPeakUsageInHemisphere
Indicates that the time period of highest usage or activity for something occurs within a specified hemisphere (e.g., Northern or Southern).
-
C.
hasCountryContext
Indicates that something is associated with, interpreted within, or relevant to a specific country or national context.
-
D.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
E.
hasCountry
Indicates that one entity possesses, is associated with, or is located within a specific country.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.