Triple
T16667859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardinal-bishop of Albano |
E405029
|
entity |
| Predicate | isUnderMetropolitan |
P62665
|
FINISHED |
| Object | Bishop of Rome |
—
|
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: Bishop of Rome | Statement: [Cardinal-bishop of Albano, isUnderMetropolitan, Bishop of Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUnderMetropolitan Context triple: [Cardinal-bishop of Albano, isUnderMetropolitan, Bishop of Rome]
-
A.
isMetropolitanFor
Indicates that one entity serves as the primary metropolitan center or urban hub for another entity (such as a region, area, or service).
-
B.
isSubjectToMetropolitan
chosen
Indicates that an entity falls under the authority, jurisdiction, or governance of a metropolitan area or metropolitan-level body.
-
C.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
D.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
E.
isLocatedInMetropolitanCity
Indicates that an entity is situated within a metropolitan city area.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9e9a208190afab499897ce4361 |
completed | April 18, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.