Triple
T13427368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaqui language |
E313515
|
entity |
| Predicate | hasLearningResources |
P10464
|
FINISHED |
| Object | community-based language programs |
—
|
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: community-based language programs | Statement: [Yaqui language, hasLearningResources, community-based language programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningResources Context triple: [Yaqui language, hasLearningResources, community-based language programs]
-
A.
hasEducationalMaterial
chosen
Indicates that an entity provides, contains, or is associated with educational content or learning resources for another entity.
-
B.
hasEducationalLink
Indicates that there is an educational relationship or connection between two entities, such as teaching, learning, training, or academic affiliation.
-
C.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
D.
hasExercises
Indicates that something includes, provides, or is associated with one or more exercises.
-
E.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.