Triple
T8328118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aviatrix Trophy |
E195005
|
entity |
| Predicate | hasNotableRecipientType |
P42372
|
FINISHED |
| Object | female pilot |
—
|
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: female pilot | Statement: [Aviatrix Trophy, hasNotableRecipientType, female pilot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableRecipientType Context triple: [Aviatrix Trophy, hasNotableRecipientType, female pilot]
-
A.
notableRecipientType
Indicates that an entity is notably recognized as a recipient of something (such as an award, honor, or distinction) of a specified type.
-
B.
hasTypeOfRecipient
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
C.
notableRecipient
Indicates that an entity has received a notable award, honor, or recognition from another entity.
-
D.
hasRecipientRole
Indicates that a specified entity serves as the recipient or target role in a given interaction, transaction, or relationship.
-
E.
hasNotableBearersType
chosen
Indicates that an entity has notable bearers belonging to a specified type or category.
- 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f8243288190b1ae74d69395fc91 |
completed | March 31, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:56 p.m.