Triple
T12325115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLEP exams |
E293808
|
entity |
| Predicate | examDuration |
P40755
|
FINISHED |
| Object | approximately 90 minutes for many exams |
—
|
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: approximately 90 minutes for many exams | Statement: [CLEP exams, examDuration, approximately 90 minutes for many exams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examDuration Context triple: [CLEP exams, examDuration, approximately 90 minutes for many exams]
-
A.
examTime
Indicates the scheduled time at which an exam is to take place.
-
B.
intendedDuration
chosen
Indicates the planned or expected length of time for which an action, event, or state is meant to occur or remain in effect.
-
C.
eraDuration
Indicates the length of time that a particular era or period spans.
-
D.
examType
Indicates the specific category or format of an exam associated with an assessment or testing event.
-
E.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.