Triple
T18089601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chesterfield Inlet |
E432929
|
entity |
| Predicate | hasPrimarySchoolLevel |
P130394
|
FINISHED |
| Object | elementary education |
—
|
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: elementary education | Statement: [Chesterfield Inlet, hasPrimarySchoolLevel, elementary education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySchoolLevel Context triple: [Chesterfield Inlet, hasPrimarySchoolLevel, elementary education]
-
A.
hasPrimaryEducationFacilityType
Indicates the type or category of primary education facility associated with an entity.
-
B.
primarySchool
Indicates that one entity serves as the primary (elementary) school attended by, associated with, or designated for the other entity.
-
C.
hasLowerSchoolEntry
Indicates that an entity is associated with or linked to a specific lower-level school at which it begins or began schooling.
-
D.
primaryYearLevel
Indicates the main or principal year level associated with an entity, such as a student, course, or program.
-
E.
primaryStudentType
Indicates the main or most characteristic type or category of student associated with an 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd17ba98819085a15e8593d98259 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:27 a.m.