Triple
T2350213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fresno City College |
E47429
|
entity |
| Predicate | hasDurationOfPrograms |
P24633
|
FINISHED |
| Object | two years for typical associate degree |
—
|
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: two years for typical associate degree | Statement: [Fresno City College, hasDurationOfPrograms, two years for typical associate degree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDurationOfPrograms Context triple: [Fresno City College, hasDurationOfPrograms, two years for typical associate degree]
-
A.
programLength
chosen
Indicates the duration or total length of a program, typically measured in time or size.
-
B.
hasPublicProgram
Indicates that an entity offers or participates in a program or initiative that is accessible to the general public.
-
C.
hasOfficialDuration
Indicates the formally defined length of time associated with an event, process, or entity.
-
D.
hasProgramme
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
E.
hasEpisodeLengthType
Indicates the type or category of duration associated with an episode (e.g., standard length, short, extended).
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.