Triple
T5429293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kettering University |
E121442
|
entity |
| Predicate | hasProgramCharacteristic |
P274
|
FINISHED |
| Object | mandatory cooperative work terms |
—
|
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: mandatory cooperative work terms | Statement: [Kettering University, hasProgramCharacteristic, mandatory cooperative work terms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProgramCharacteristic Context triple: [Kettering University, hasProgramCharacteristic, mandatory cooperative work terms]
-
A.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
hasProgramCode
Indicates that an entity is associated with a specific program identifier or code used to reference or classify it within a system.
-
C.
hasPlanningCharacteristic
Indicates that an entity possesses a specific feature, quality, or attribute related to planning activities or processes.
-
D.
hasProgramCategory
Indicates that a program is classified under a specific category or type of program.
-
E.
hasPerformerCharacteristic
Indicates that a performer possesses a particular attribute, quality, or characteristic.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.