Triple
T22863578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universidad Tecnológica de Chile INACAP |
E566989
|
entity |
| Predicate | hasCampusDistribution |
P24734
|
FINISHED |
| Object | across the country |
—
|
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: across the country | Statement: [Universidad Tecnológica de Chile INACAP, hasCampusDistribution, across the country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusDistribution Context triple: [Universidad Tecnológica de Chile INACAP, hasCampusDistribution, across the country]
-
A.
campusDistribution
chosen
Indicates how resources, activities, or populations are allocated or spread across different campuses within an institution.
-
B.
hasCampusState
Indicates that an institution’s campus is located within a specified state or state-level administrative region.
-
C.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
D.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
E.
hasMultipleCampuses
Indicates that an educational institution operates more than one physical campus location.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eff1c18819081dc9dfc1816f746 |
completed | April 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69eed2d507c08190895ed971af0fc755 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:38 p.m.