Triple
T1326653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middlebury College |
E28342
|
entity |
| Predicate | formerGenderRestriction |
P14517
|
FINISHED |
| Object | originally men 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: originally men only | Statement: [Middlebury College, formerGenderRestriction, originally men only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerGenderRestriction Context triple: [Middlebury College, formerGenderRestriction, originally men only]
-
A.
formerGenderAdmission
chosen
Indicates that an institution previously admitted a particular gender but no longer does so.
-
B.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
C.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
D.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
E.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c0a22881909eff0fc6c91a5f41 |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.