Triple
T37179870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Episcopal Diocese of South West Virginia |
E921161
|
entity |
| Predicate | isGeographicallyDefined |
P90717
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Episcopal Diocese of South West Virginia, isGeographicallyDefined, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGeographicallyDefined Context triple: [Episcopal Diocese of South West Virginia, isGeographicallyDefined, yes]
-
A.
geographicallyDefinedAs
chosen
Indicates that one entity’s geographic extent, boundaries, or location is defined or characterized in terms of another geographic entity.
-
B.
isGeographicallySpecific
Indicates that something is limited to or uniquely associated with a particular geographic location or area.
-
C.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
D.
geographicCriterion
Indicates that the relationship or selection is determined based on geographic factors, such as location, region, or spatial boundaries.
-
E.
isGeographicalEntity
Indicates that something exists as a distinct geographic feature, area, or place within physical space.
- 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_69f76ea250bc819083f28d81de25cd0c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.