Triple
T38218327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whirlpool Aero Car |
E1010743
|
entity |
| Predicate | doesNotLandIn |
P171939
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Whirlpool Aero Car, doesNotLandIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotLandIn Context triple: [Whirlpool Aero Car, doesNotLandIn, United States]
-
A.
doesNotEnter
Indicates that one entity refrains from or fails to go into or cross the boundary of another entity or location.
-
B.
doesNotCross
chosen
Indicates that one entity remains entirely separate from another and does not intersect, traverse, or pass through it in any way.
-
C.
doesNotTry
Indicates that an entity makes no attempt to perform a particular action or engage in a specified activity.
-
D.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
E.
doesNotAimFor
Indicates that one entity does not direct effort, intention, or purpose toward achieving, obtaining, or targeting another entity or outcome.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: May 3, 2026, 4:30 p.m.