Triple
T12338909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Joseph's College of Maine |
E294166
|
entity |
| Predicate | currentGenderPolicy |
P277
|
FINISHED |
| Object | coeducational |
—
|
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: coeducational | Statement: [Saint Joseph's College of Maine, currentGenderPolicy, coeducational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentGenderPolicy Context triple: [Saint Joseph's College of Maine, currentGenderPolicy, coeducational]
-
A.
hasGenderPolicy
chosen
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
demographicPolicy
Indicates a relationship where an authority or organization establishes or applies rules and measures intended to influence the size, structure, or composition of a population.
-
C.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
D.
currentPolicy
Indicates that a given policy is the one presently in effect or actively governing the relevant context.
-
E.
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.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f678698819091462b44ff3435f6 |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.