Triple
T1644995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Querétaro |
E35559
|
entity |
| Predicate | hasSignificantIndustryCluster |
P20603
|
FINISHED |
| Object | aerospace cluster in Querétaro |
—
|
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: aerospace cluster in Querétaro | Statement: [Querétaro, hasSignificantIndustryCluster, aerospace cluster in Querétaro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantIndustryCluster Context triple: [Querétaro, hasSignificantIndustryCluster, aerospace cluster in Querétaro]
-
A.
isPartOfEconomicCluster
Indicates that an entity belongs to, or is included within, a larger economic cluster or grouping based on economic relationships or activities.
-
B.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
C.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
D.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
-
E.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.