Triple
T13050915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owens College |
E327444
|
entity |
| Predicate | admittedGender |
P14517
|
FINISHED |
| Object | initially male students only |
—
|
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: initially male students only | Statement: [Owens College, admittedGender, initially male students only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: admittedGender Context triple: [Owens College, admittedGender, initially male students only]
-
A.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
B.
formerGenderAdmission
chosen
Indicates that an institution previously admitted a particular gender but no longer does so.
-
C.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
D.
admittedMen
Indicates that one entity has granted admission or entry to another entity who is male.
-
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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:57 p.m.