Triple
T35088232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Short Mayo Composite project |
E1012637
|
entity |
| Predicate | aircraftTypeTested |
P17100
|
FINISHED |
| Object | flying boat |
—
|
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: flying boat | Statement: [Short Mayo Composite project, aircraftTypeTested, flying boat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTypeTested Context triple: [Short Mayo Composite project, aircraftTypeTested, flying boat]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
notableAircraftTested
chosen
Indicates that the subject conducted tests or evaluations on the specified aircraft, which is considered notable or significant.
-
C.
poweredAircraftType
Indicates that one entity is a type or category of aircraft that is propelled by an onboard power source (e.g., engines), as opposed to being unpowered.
-
D.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
-
E.
aircraftTypeManaged
Indicates that one entity is responsible for managing or overseeing a particular type or category of aircraft.
- 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_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.