Triple
T6352747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan City of Genoa |
E142914
|
entity |
| Predicate | isMetropolitanAreaFor |
P42426
|
FINISHED |
| Object | city of Genoa |
—
|
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: city of Genoa | Statement: [Metropolitan City of Genoa, isMetropolitanAreaFor, city of Genoa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMetropolitanAreaFor Context triple: [Metropolitan City of Genoa, isMetropolitanAreaFor, city of Genoa]
-
A.
metropolitanAreaWith
chosen
Indicates that one entity is a metropolitan area that includes, is associated with, or encompasses the other entity.
-
B.
isMetropolitanCoreOf
Indicates that one area functions as the central, most urbanized core within a larger metropolitan region or system.
-
C.
metropolitanOf
Indicates that one place serves as the primary metropolitan center or core urban area for another place or region.
-
D.
hasMetropolitanAreaName
Indicates that an entity is associated with a metropolitan area identified by a specific name.
-
E.
representsMetropolitanArea
Indicates that one entity serves as or corresponds to the metropolitan area associated with another entity.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067dd3c74819085a164b750094c46 |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.