Triple
T1254558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vetus Ordo |
E26956
|
entity |
| Predicate | typicalUseRegion |
P15483
|
FINISHED |
| Object | worldwide Catholic dioceses before Vatican II |
—
|
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 Catholic dioceses before Vatican II | Statement: [Vetus Ordo, typicalUseRegion, worldwide Catholic dioceses before Vatican II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseRegion Context triple: [Vetus Ordo, typicalUseRegion, worldwide Catholic dioceses before Vatican II]
-
A.
hasTypicalUsageRegion
chosen
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
B.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
C.
landingRegion
Indicates the area or zone where an object or entity comes to rest or makes contact after moving or descending.
-
D.
typicalDestinationsRegion
Indicates that a region is a common or characteristic destination area associated with something (such as travelers, routes, or activities).
-
E.
typicalRegionRights
Indicates that certain rights or permissions are characteristic or standard for a given region.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bfa5a4cc819093ed686619b572d8 |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6c977c8190a2bf3e8b67a59beb |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.