Triple
T27781824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyberchase |
E699351
|
entity |
| Predicate | intendedLearningDomain |
P96519
|
FINISHED |
| Object | STEM |
—
|
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: STEM | Statement: [Cyberchase, intendedLearningDomain, STEM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedLearningDomain Context triple: [Cyberchase, intendedLearningDomain, STEM]
-
A.
hasEducationalScope
Indicates that an entity is associated with a particular educational level, range, or context that defines the scope of its relevance or applicability.
-
B.
learnedIn
Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
-
C.
trainingDomain
Indicates that an entity is associated with or operates within a particular field, area, or domain of training.
-
D.
educationalFocus
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
-
E.
primarySubjectArea
chosen
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 5:10 p.m.