Triple
T31726730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pesquería, Nuevo León |
E809737
|
entity |
| Predicate | hasAutomotivePresence |
P149918
|
FINISHED |
| Object | Kia Motors Mexico plant |
—
|
NE NERFINISHED |
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: Kia Motors Mexico plant | Statement: [Pesquería, Nuevo León, hasAutomotivePresence, Kia Motors Mexico plant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomotivePresence Context triple: [Pesquería, Nuevo León, hasAutomotivePresence, Kia Motors Mexico plant]
-
A.
hasAutomotiveIndustryBrand
Indicates that an entity possesses, is associated with, or operates a specific brand within the automotive industry.
-
B.
hasAutomotiveCluster
Indicates that an entity possesses or is associated with a concentration of automotive-related industries, organizations, or activities.
-
C.
associatedWithAutomotiveIndustry
chosen
Indicates a relationship in which an entity is connected or relevant to the automotive industry, such as through products, services, operations, or affiliations.
-
D.
automotiveClassSupported
Indicates that a particular automotive class or category is supported or compatible within a given context or system.
-
E.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
- 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_69f348e009c8819095d77df52c645b9c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: April 30, 2026, 11:20 p.m.