Triple
T8454990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hana High and Elementary School |
E199897
|
entity |
| Predicate | campusConfiguration |
P82732
|
FINISHED |
| Object | single campus for K–12 |
—
|
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: single campus for K–12 | Statement: [Hana High and Elementary School, campusConfiguration, single campus for K–12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusConfiguration Context triple: [Hana High and Elementary School, campusConfiguration, single campus for K–12]
-
A.
mainCampusSetting
Indicates that an institution’s primary or central campus is used as the setting or location for the related activity or context.
-
B.
governsCampus
Indicates that one entity has administrative or authoritative control over the operations and policies of a campus.
-
C.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
D.
campus1
Indicates a relationship where an entity is identified as a campus or is located on/associated with a particular campus.
-
E.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48ca9988190b60ebd09a135194d |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:10 p.m.