Triple
T35701919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winnie Mae Fain |
E1031607
|
entity |
| Predicate | hasNameInAircraftContext |
P112363
|
FINISHED |
| Object | Winnie Mae |
—
|
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: Winnie Mae | Statement: [Winnie Mae Fain, hasNameInAircraftContext, Winnie Mae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInAircraftContext Context triple: [Winnie Mae Fain, hasNameInAircraftContext, Winnie Mae]
-
A.
hasSymbolicNameForAirRoute
Indicates that an air route is associated with a specific symbolic or designated name used to identify it.
-
B.
aircraftNamedIs
chosen
Indicates that a specific aircraft has the given name or designation.
-
C.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
-
D.
referredAircraftCommonName
Indicates that one entity mentions or identifies an aircraft using its commonly known name.
-
E.
usedInAviationCodeContext
Indicates that something is employed or referenced within the context of aviation-related codes or coding systems.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff5285ed74819097e6e2a9084a079a |
completed | May 9, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69ff51fbe28881908ac8417dff9db81a |
completed | May 9, 2026, 3:25 p.m. |
Created at: May 3, 2026, 4:05 p.m.