Triple
T20929487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 1 Recruit Training Unit RAAF |
E515429
|
entity |
| Predicate | hasGenderInclusiveRole |
P136236
|
FINISHED |
| Object | airmen and airwomen |
—
|
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: airmen and airwomen | Statement: [No. 1 Recruit Training Unit RAAF, hasGenderInclusiveRole, airmen and airwomen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderInclusiveRole Context triple: [No. 1 Recruit Training Unit RAAF, hasGenderInclusiveRole, airmen and airwomen]
-
A.
hasGenderRole
Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
-
B.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
C.
hasGenderRepresentation
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
-
D.
hasGenderNeutralEligibility
Indicates that an entity is eligible or applicable in a way that does not depend on or specify a particular gender.
-
E.
includesBothGenders
chosen
Indicates that the referenced group, set, or category contains members of both male and female genders.
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f6545f8c81908a8c2f0e8d7b060e |
completed | April 21, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:49 p.m.