Triple
T26650443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowell Mather |
E669033
|
entity |
| Predicate | mechanicalExpertise |
P161086
|
FINISHED |
| Object | aircraft maintenance |
—
|
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: aircraft maintenance | Statement: [Lowell Mather, mechanicalExpertise, aircraft maintenance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mechanicalExpertise Context triple: [Lowell Mather, mechanicalExpertise, aircraft maintenance]
-
A.
featuresMechanic
Indicates that something includes or incorporates a particular mechanic as part of its design or functionality.
-
B.
mechanicalFunction
Indicates that one entity serves as the mechanical role, operation, or function performed by another entity or system.
-
C.
mechanicalCompatibility
Indicates that two entities can function together properly from a mechanical standpoint, without interference, damage, or performance issues.
-
D.
mechanicalDesign
Indicates that one entity is responsible for or associated with the mechanical design or engineering configuration of another entity.
-
E.
hasMechanicalFeature
Indicates that one entity possesses, includes, or is characterized by a specific mechanical component, attribute, or functionality.
- 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f616798e408190b271a85ebdb78cd1 |
completed | May 2, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60f24ed608190bffe6c6084fc2f7a |
completed | May 2, 2026, 2:50 p.m. |
Created at: April 27, 2026, 2:32 a.m.