Triple
T28757568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endicott College |
E731711
|
entity |
| Predicate | originalGenderAdmissionPolicy |
P14517
|
FINISHED |
| Object | women's college |
—
|
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: women's college | Statement: [Endicott College, originalGenderAdmissionPolicy, women's college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalGenderAdmissionPolicy Context triple: [Endicott College, originalGenderAdmissionPolicy, women's college]
-
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.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
D.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
E.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
- 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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
Created at: April 28, 2026, 6:10 a.m.