Triple
T10992669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic dioceses |
E259787
|
entity |
| Predicate | canBeGroupedIn |
P35715
|
FINISHED |
| Object | ecclesiastical province |
—
|
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: ecclesiastical province | Statement: [Roman Catholic dioceses, canBeGroupedIn, ecclesiastical province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeGroupedIn Context triple: [Roman Catholic dioceses, canBeGroupedIn, ecclesiastical province]
-
A.
groupedInto
Indicates that multiple entities are collected or organized together as members of a common group or category.
-
B.
areSometimesGroupedWith
Indicates that two or more entities are occasionally but not consistently classified, treated, or considered together as part of the same group.
-
C.
canBelongTo
chosen
Indicates that something is capable of being a member or part of a particular group, category, or owner.
-
D.
isNarrativelyGroupedWith
Indicates that two or more elements are treated as part of the same narrative unit, sequence, or storyline within a larger context.
-
E.
groupingType
Indicates how multiple entities are categorized or clustered together based on a shared grouping criterion.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d32f9081909def643571499521 |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.