Triple
T6753844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cornell College |
E154402
|
entity |
| Predicate | calendarUnitLength |
P42651
|
FINISHED |
| Object | approximately 3.5 weeks per course |
—
|
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 3.5 weeks per course | Statement: [Cornell College, calendarUnitLength, approximately 3.5 weeks per course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: calendarUnitLength Context triple: [Cornell College, calendarUnitLength, approximately 3.5 weeks per course]
-
A.
quarterLength
Indicates that one entity specifies the length or duration of a quarter (e.g., a time period or segment) associated with another entity.
-
B.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
C.
hasWeekLength
Indicates the duration of a week associated with an entity, typically expressed as a number of days.
-
D.
hasDayUnit
Indicates that something is measured, expressed, or quantified in units of days.
-
E.
timeCharacteristic
chosen
Indicates a relationship where one entity specifies a temporal property, feature, or constraint that characterizes another entity or event.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.