Triple
T2403468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maasai language |
E50220
|
entity |
| Predicate | hasLearningResource |
P10464
|
FINISHED |
| Object | Maasai language primers |
—
|
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: Maasai language primers | Statement: [Maasai language, hasLearningResource, Maasai language primers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningResource Context triple: [Maasai language, hasLearningResource, Maasai language primers]
-
A.
hasEducationalMaterial
chosen
Indicates that an entity provides, contains, or is associated with educational content or learning resources for another entity.
-
B.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
C.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
D.
educationalActivity
Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
-
E.
hasEducationalSupportFrom
Indicates that one entity receives educational assistance, guidance, or resources from another 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.