Triple
T2624145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Córdoba, Argentina |
E59076
|
entity |
| Predicate | universityCharacteristic |
P42298
|
FINISHED |
| Object | one of the oldest universities in the Americas |
—
|
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: one of the oldest universities in the Americas | Statement: [Córdoba, Argentina, universityCharacteristic, one of the oldest universities in the Americas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: universityCharacteristic Context triple: [Córdoba, Argentina, universityCharacteristic, one of the oldest universities in the Americas]
-
A.
memberInstitutionCharacteristic
Indicates that a specific characteristic or attribute is associated with a member institution within a larger organization or system.
-
B.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
-
C.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
D.
university2
Indicates a relationship where an entity is a university associated with, attended by, or otherwise linked to another entity.
-
E.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd80f48888190afdf7e3e042157d0 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abdac82b688190886a6ec2d6e2abc7 |
completed | March 7, 2026, 7:59 a.m. |
Created at: March 6, 2026, 9:50 p.m.