Triple
T7030569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conway’s Doomsday algorithm |
E163256
|
entity |
| Predicate | teachingUse |
P63933
|
FINISHED |
| Object | illustrate modular arithmetic in a practical context |
—
|
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: illustrate modular arithmetic in a practical context | Statement: [Conway’s Doomsday algorithm, teachingUse, illustrate modular arithmetic in a practical context]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingUse Context triple: [Conway’s Doomsday algorithm, teachingUse, illustrate modular arithmetic in a practical context]
-
A.
usesInTeaching
chosen
Indicates that an agent employs a particular resource, method, or material as part of their teaching activities.
-
B.
coreTeaching
Indicates that an entity serves as a primary or foundational teaching or instructional activity for another entity.
-
C.
educationUse
Indicates the use or application of something specifically for educational purposes or in an educational context.
-
D.
definedTeaching
Indicates that one entity has formally specified or established the teaching content, method, or curriculum for another entity.
-
E.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:35 p.m.