Triple
T910730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Community Colleges System |
E19650
|
entity |
| Predicate | typicalProgramLength |
P18065
|
FINISHED |
| Object | two-year 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: two-year programs | Statement: [California Community Colleges System, typicalProgramLength, two-year programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalProgramLength Context triple: [California Community Colleges System, typicalProgramLength, two-year programs]
-
A.
typicalRecordingDuration
Indicates the usual or standard length of time that something is recorded.
-
B.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
C.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
D.
hasEpisodeRuntime
Indicates the duration of time that each individual episode of a series or show runs.
-
E.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.