Triple
T25053423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Querétaro metropolitan area |
E627446
|
entity |
| Predicate | isUrbanAndIndustrialHub |
P157920
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Querétaro metropolitan area, isUrbanAndIndustrialHub, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanAndIndustrialHub Context triple: [Querétaro metropolitan area, isUrbanAndIndustrialHub, true]
-
A.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
B.
isUrbanCenter
Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
-
C.
isUrbanCentreFor
Indicates that one place functions as the primary urban hub or central city serving another area or population.
-
D.
isTransportCenterOf
Indicates that a location functions as a primary hub or central node for transportation activities serving another area or network.
-
E.
isPlannedIndustrialCity
Indicates that a city has been intentionally designed and developed primarily for industrial purposes according to a formal plan.
- F. None of above. chosen
Provenance (4 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f454a4473081909416bc98dfe96233 |
completed | May 1, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 18, 2026, 6:09 a.m.