Triple
T3992192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagga Wagga Superior Public School |
E87015
|
entity |
| Predicate | hasFormerPupilWhoBecame |
P51
|
FINISHED |
| Object | Field Marshal |
—
|
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: Field Marshal | Statement: [Wagga Wagga Superior Public School, hasFormerPupilWhoBecame, Field Marshal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerPupilWhoBecame Context triple: [Wagga Wagga Superior Public School, hasFormerPupilWhoBecame, Field Marshal]
-
A.
hasFormerPupilRole
Indicates that an entity previously held the role or position of a pupil or student in relation to another entity.
-
B.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
-
D.
hasAlumni
chosen
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
E.
hadAlumniRole
Indicates that an entity previously held a role or position as an alumnus/alumna of another entity (such as an institution or organization).
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.