Triple
T14771421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilsonville High School |
E347142
|
entity |
| Predicate | suburbanCampus |
P115727
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Wilsonville High School, suburbanCampus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanCampus Context triple: [Wilsonville High School, suburbanCampus, true]
-
A.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
B.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
-
C.
mainCampusNeighborhood
Indicates that a neighborhood is the primary surrounding or associated area of a campus.
-
D.
residentialCampus
Indicates that an educational institution’s campus includes on-site housing where students live as part of the campus community.
-
E.
secondaryCampus
Indicates that an institution or organization has an additional, non-primary campus located at a different site.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81334e08190a77d760e507d00ed |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.