Triple
T27782092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hacker |
E699357
|
entity |
| Predicate | intendedEducationalContext |
P55744
|
FINISHED |
| Object | mathematics 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: mathematics education | Statement: [The Hacker, intendedEducationalContext, mathematics education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedEducationalContext Context triple: [The Hacker, intendedEducationalContext, mathematics education]
-
A.
educationalContext
chosen
Indicates the situational or institutional setting in which an educational activity, interaction, or resource takes place.
-
B.
hasEducationalScope
Indicates that an entity is associated with a particular educational level, range, or context that defines the scope of its relevance or applicability.
-
C.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
D.
isEducational
Indicates that something serves to teach, instruct, or facilitate learning for an audience.
-
E.
hasEducationalDimension
Indicates that something includes, involves, or contributes to an educational aspect, purpose, or impact within the relationship or context described.
- 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_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 27, 2026, 5:10 p.m.