Triple
T3135269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atikamekw language |
E65511
|
entity |
| Predicate | hasEducationalUseIn |
P23523
|
FINISHED |
| Object | band-controlled schools |
—
|
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: band-controlled schools | Statement: [Atikamekw language, hasEducationalUseIn, band-controlled schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalUseIn Context triple: [Atikamekw language, hasEducationalUseIn, band-controlled schools]
-
A.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
usedInEducationIn
chosen
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
C.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
D.
educationUse
Indicates the use or application of something specifically for educational purposes or in an educational context.
-
E.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5637de0819089393429c4017298 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.