Triple
T2663848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euler’s polyhedron formula |
E54784
|
entity |
| Predicate | hasDidacticUse |
P27488
|
FINISHED |
| Object | introductory example in topology courses |
—
|
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: introductory example in topology courses | Statement: [Euler’s polyhedron formula, hasDidacticUse, introductory example in topology courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDidacticUse Context triple: [Euler’s polyhedron formula, hasDidacticUse, introductory example in topology courses]
-
A.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
didacticPurpose
chosen
Indicates that something is intended to teach, instruct, or convey educational content or guidance.
-
C.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
D.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
E.
hasEducationalMaterial
Indicates that an entity provides, contains, or is associated with educational content or learning resources for 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96dba44819085c3e651afba7806 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.