Triple
T6804782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Puerto Rico Medical Sciences Campus |
E156275
|
entity |
| Predicate | campusSpecialization |
P36070
|
FINISHED |
| Object | health sciences |
—
|
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: health sciences | Statement: [University of Puerto Rico Medical Sciences Campus, campusSpecialization, health sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusSpecialization Context triple: [University of Puerto Rico Medical Sciences Campus, campusSpecialization, health sciences]
-
A.
isSpecializedCampus
chosen
Indicates that a campus is dedicated to a specific field, discipline, or set of specialized programs rather than offering a broad, general curriculum.
-
B.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
C.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
D.
campus1
Indicates a relationship where an entity is identified as a campus or is located on/associated with a particular campus.
-
E.
campusCoreOf
Indicates that one entity serves as the central or primary campus area or component of another entity.
- 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_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ea459c819095388218d53c250a |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.