Triple
T33580768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eyak language |
E860141
|
entity |
| Predicate | hasLearningMaterials |
P10464
|
FINISHED |
| Object | pedagogical grammars |
—
|
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: pedagogical grammars | Statement: [Eyak language, hasLearningMaterials, pedagogical grammars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningMaterials Context triple: [Eyak language, hasLearningMaterials, pedagogical grammars]
-
A.
hasEducationalMaterial
chosen
Indicates that an entity provides, contains, or is associated with educational content or learning resources for another entity.
-
B.
hasExercises
Indicates that something includes, provides, or is associated with one or more exercises.
-
C.
hasMaterialResource
Indicates that an entity possesses, controls, or has access to a tangible material resource.
-
D.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
E.
learnedIn
Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: May 1, 2026, 1:40 a.m.