Triple
T135816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of La Serena |
E2742
|
entity |
| Predicate | hasStudentBodyType |
P5246
|
FINISHED |
| Object | full-time students |
—
|
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: full-time students | Statement: [University of La Serena, hasStudentBodyType, full-time students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentBodyType Context triple: [University of La Serena, hasStudentBodyType, full-time students]
-
A.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
-
B.
hasAwardingBodyType
Indicates that an entity has an associated type or category describing the kind of organization or body that grants an award.
-
C.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
D.
typeOfBody
Indicates that one entity is the classification or kind of physical body that the other entity is.
-
E.
typicalBodyType
Indicates that one entity is the usual or characteristic body type associated with another entity.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.