Triple
T37826685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas community colleges |
E943078
|
entity |
| Predicate | offerProgramType |
P100436
|
FINISHED |
| Object | technical training 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: technical training programs | Statement: [Kansas community colleges, offerProgramType, technical training programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offerProgramType Context triple: [Kansas community colleges, offerProgramType, technical training programs]
-
A.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
B.
offersProgramCategory
chosen
Indicates that an entity provides or makes available a specific category of program.
-
C.
offersProgramMode
Indicates that one entity provides or makes available a specific program mode or operational mode to another entity or for a particular context.
-
D.
offersProgramComponent
Indicates that an entity provides or makes available a specific program component as part of its offerings.
-
E.
offersProgrammeField
Indicates that an educational provider or programme offers a specific field or area of study as part of its curriculum.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: May 3, 2026, 4:19 p.m.