Triple
T5112483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taking to the Air |
E115247
|
entity |
| Predicate | intendedEducationalUse |
P27185
|
FINISHED |
| Object | science education |
—
|
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: science education | Statement: [Taking to the Air, intendedEducationalUse, science education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedEducationalUse Context triple: [Taking to the Air, intendedEducationalUse, science education]
-
A.
hasEducationalUse
chosen
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
C.
educationUse
Indicates the use or application of something specifically for educational purposes or in an educational context.
-
D.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
E.
didacticPurpose
Indicates that something is intended to teach, instruct, or convey educational content or guidance.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ca57e881908242def2a032902e |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.