Triple
T6194540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King's College School, London |
E138476
|
entity |
| Predicate | genderAdmissionSixthForm |
P16158
|
FINISHED |
| Object | co-educational |
—
|
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: co-educational | Statement: [King's College School, London, genderAdmissionSixthForm, co-educational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderAdmissionSixthForm Context triple: [King's College School, London, genderAdmissionSixthForm, co-educational]
-
A.
admissionGender
chosen
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
B.
formerGenderAdmission
Indicates that an institution previously admitted a particular gender but no longer does so.
-
C.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
D.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062443cec81909dc9bafea2f5e7d4 |
completed | March 22, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c055fbce1081908805fd12e242ab96 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:19 p.m.