Triple
T38598106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piper PA-28 Cherokee family |
E934135
|
entity |
| Predicate | engineManufacturerCommon |
P86295
|
FINISHED |
| Object | Lycoming Engines |
—
|
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: Lycoming Engines | Statement: [Piper PA-28 Cherokee family, engineManufacturerCommon, Lycoming Engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engineManufacturerCommon Context triple: [Piper PA-28 Cherokee family, engineManufacturerCommon, Lycoming Engines]
-
A.
engineBrand
chosen
Indicates that one entity is the brand or manufacturer of the engine used by another entity.
-
B.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
-
C.
carManufacturer
Indicates that one entity is the company that produces or manufactures the car represented by the other entity.
-
D.
engineManufacturerTested
Indicates that an engine manufacturer has been subjected to and has undergone a testing or evaluation process.
-
E.
alsoManufacturedBy
Indicates that an item or product is produced by an additional manufacturer beyond the primary or previously mentioned one.
- 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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.