Triple
T1546503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silicon Valley of Mexico |
E32988
|
entity |
| Predicate | perceivedAdvantage |
P22974
|
FINISHED |
| Object | skilled engineering workforce |
—
|
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: skilled engineering workforce | Statement: [Silicon Valley of Mexico, perceivedAdvantage, skilled engineering workforce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceivedAdvantage Context triple: [Silicon Valley of Mexico, perceivedAdvantage, skilled engineering workforce]
-
A.
notableAdvantage
Indicates that one entity possesses a significant benefit, edge, or favorable quality over another entity or in a given context.
-
B.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
C.
primaryBenefit
Indicates that one entity serves as the main or most important advantage, gain, or positive outcome associated with another entity.
-
D.
influencedPerceptionOf
chosen
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
E.
benefitsCause
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or cause.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa574094048190a2d7fc3ac904d51e |
completed | March 6, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69a907b426dc8190975c024a50955368 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.