Triple
T7431729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Catharine’s College, Cambridge |
E171504
|
entity |
| Predicate | hasGenderAdmittance |
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: [St Catharine’s College, Cambridge, hasGenderAdmittance, co-educational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderAdmittance Context triple: [St Catharine’s College, Cambridge, hasGenderAdmittance, co-educational]
-
A.
admissionGender
chosen
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
B.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
C.
formerGenderAdmission
Indicates that an institution previously admitted a particular gender but no longer does so.
-
D.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
-
E.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f324afac8190b34fcac95fd57410 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.