Triple
T33103990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forest Hill School |
E847134
|
entity |
| Predicate | hasPupilGenderPolicy |
P277
|
FINISHED |
| Object | single-sex up to age 16 |
—
|
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: single-sex up to age 16 | Statement: [Forest Hill School, hasPupilGenderPolicy, single-sex up to age 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPupilGenderPolicy Context triple: [Forest Hill School, hasPupilGenderPolicy, single-sex up to age 16]
-
A.
hasPupilsGender
Indicates that an entity has pupils whose gender is specified or characterized in some way.
-
B.
hasGenderPolicy
chosen
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
C.
hasCoeducation
Indicates that an educational institution includes both male and female students together in its instructional programs.
-
D.
studentDemographicPolicy
Indicates a policy that governs or affects students based on their demographic characteristics or composition.
-
E.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
- 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: May 1, 2026, 1:26 a.m.