Triple
T3372556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evergreen State College |
E70987
|
entity |
| Predicate | curriculumFeature |
P17044
|
FINISHED |
| Object | interdisciplinary programs |
—
|
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: interdisciplinary programs | Statement: [Evergreen State College, curriculumFeature, interdisciplinary programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curriculumFeature Context triple: [Evergreen State College, curriculumFeature, interdisciplinary programs]
-
A.
offersCurriculum
Indicates that one entity provides or makes available a specific curriculum to another entity.
-
B.
usesCurriculum
Indicates that one entity adopts or applies a particular curriculum as the basis for its instruction, training, or educational activities.
-
C.
educationSystemCharacteristic
chosen
Indicates a characteristic, feature, or attribute that describes an education system.
-
D.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
E.
educationalFocus
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bdcf70819087fc7e00fbd61e0d |
completed | March 8, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69ada433059881908e46f38cc5f40a32 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.