Triple
T21714403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Andrew’s School |
E535985
|
entity |
| Predicate | studentBodyGender |
P113101
|
FINISHED |
| Object | coeducational |
—
|
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: coeducational | Statement: [St. Andrew’s School, studentBodyGender, coeducational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentBodyGender Context triple: [St. Andrew’s School, studentBodyGender, coeducational]
-
A.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
-
B.
hasPupilsGender
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
C.
genderOfMembers
chosen
Indicates the gender or genders associated with the members of a group or organization.
-
D.
genderRatio
Indicates the proportional relationship between different genders within a given group or population.
-
E.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5369be88190bafc10863d4d1bd7 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.