Triple
T29975093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IUT (Institut universitaire de technologie) |
E761421
|
entity |
| Predicate | typicalDegreeLength |
P204095
|
FINISHED |
| Object | 2 to 3 years |
—
|
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: 2 to 3 years | Statement: [IUT (Institut universitaire de technologie), typicalDegreeLength, 2 to 3 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDegreeLength Context triple: [IUT (Institut universitaire de technologie), typicalDegreeLength, 2 to 3 years]
-
A.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
B.
typicalDegreeName
Indicates the standard or commonly used academic degree title associated with an educational program or qualification.
-
C.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
-
D.
typicalDegreeLevels
Indicates the usual or commonly expected academic degree levels associated with a given entity or context.
-
E.
hasNumberOfDegrees
Indicates the quantity of academic degrees that an entity possesses.
- F. None of above. chosen
Provenance (4 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_69f22467626081908d5afea489590e96 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a03232efd8481908ee25447a29ee20b |
completed | May 12, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_6a032269dcb08190907c965c28145b77 |
completed | May 12, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_6a03232e53788190abf17396e8d02dbf |
completed | May 12, 2026, 12:55 p.m. |
Created at: April 29, 2026, 6:33 p.m.