Triple
T9835783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glendower Preparatory School |
E239097
|
entity |
| Predicate | singleSexOrCoed |
P32136
|
FINISHED |
| Object | single-sex |
—
|
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 | Statement: [Glendower Preparatory School, singleSexOrCoed, single-sex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: singleSexOrCoed Context triple: [Glendower Preparatory School, singleSexOrCoed, single-sex]
-
A.
isSingleSex
chosen
Indicates that the entity involves or is restricted to only one biological sex or gender, rather than being mixed or coeducational.
-
B.
hasCoeducation
Indicates that an educational institution includes both male and female students together in its instructional programs.
-
C.
isUnisex
Indicates that something is suitable, designed, or intended for use by individuals of any gender.
-
D.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
E.
sexType
Indicates the specific category or type of sexual activity or sexual relationship involved between entities.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb339aa1c8190901d8e660cef49c5 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:33 p.m.