Triple
T24531472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mendoza metropolitan area |
E606821
|
entity |
| Predicate | isUrbanHubOf |
P79357
|
FINISHED |
| Object | western Argentina |
—
|
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: western Argentina | Statement: [Mendoza metropolitan area, isUrbanHubOf, western Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanHubOf Context triple: [Mendoza metropolitan area, isUrbanHubOf, western Argentina]
-
A.
isUrbanHubFor
chosen
Indicates that a location functions as a central urban focal point or primary service center for another area or population.
-
B.
isUrbanCentreFor
Indicates that one place functions as the primary urban hub or central city serving another area or population.
-
C.
isUrbanCenter
Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
-
D.
isUrbanSectionOf
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
E.
isUrbanBackdropOf
Indicates that one entity serves as the city or metropolitan background setting against which another entity is situated, depicted, or occurs.
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:25 a.m.