Triple
T33706384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulsan |
E863602
|
entity |
| Predicate | hasLargestAutomobilePlantOf |
P198739
|
FINISHED |
| Object | Hyundai Motor Ulsan 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: Hyundai Motor Ulsan Plant | Statement: [Ulsan, hasLargestAutomobilePlantOf, Hyundai Motor Ulsan Plant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargestAutomobilePlantOf Context triple: [Ulsan, hasLargestAutomobilePlantOf, Hyundai Motor Ulsan Plant]
-
A.
hasMajorAutomakerHeadquarters
Indicates that a location serves as the primary corporate headquarters for a major automobile manufacturing company.
-
B.
enteredAutomobileProduction
Indicates that an entity began manufacturing automobiles as a commercial or industrial activity.
-
C.
hasProductionFacilitiesIn
Indicates that an entity operates or owns production facilities located within a specified geographic area or jurisdiction.
-
D.
hasManufacturerHeadquartersIn
Indicates that the location specified is the place where the manufacturer’s main headquarters is situated.
-
E.
automakerParentCompany
Indicates that one company is the parent company of another company that manufactures automobiles.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff0214d7348190904688376df99bce |
completed | May 9, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69feffd62fec8190a855922c8b3c57cf |
completed | May 9, 2026, 9:35 a.m. |
| PDg | Predicate description generation | batch_69ff02141dbc8190b00bcea2aa734b3a |
completed | May 9, 2026, 9:44 a.m. |
Created at: May 1, 2026, 1:43 a.m.