Triple
T27130011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAGPS of NSW |
E681537
|
entity |
| Predicate | memberGenderFocus |
P2452
|
FINISHED |
| Object | boys |
—
|
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: boys | Statement: [AAGPS of NSW, memberGenderFocus, boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberGenderFocus Context triple: [AAGPS of NSW, memberGenderFocus, boys]
-
A.
hasGenderFocus
chosen
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
B.
genderOfMembers
Indicates the gender or genders associated with the members of a group or organization.
-
C.
bearerGender
Indicates the gender associated with the bearer in the relationship or context.
-
D.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
-
E.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 27, 2026, 9:03 a.m.