Triple
T27004059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss Maturité |
E680191
|
entity |
| Predicate | coreSubjectsInclude |
P145958
|
FINISHED |
| Object | arts or music |
—
|
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: arts or music | Statement: [Swiss Maturité, coreSubjectsInclude, arts or music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreSubjectsInclude Context triple: [Swiss Maturité, coreSubjectsInclude, arts or music]
-
A.
schoolSubject
chosen
Indicates that an entity is an academic subject taught, studied, or associated with a school or educational program.
-
B.
schoolSubjectContext
Indicates that an entity is being considered specifically in the context of a school subject or academic discipline.
-
C.
materiasQueConocen
Indicates a relationship where certain subjects or topics are known or mastered by specific entities.
-
D.
teachingSubject
Indicates that an entity is engaged in teaching or instructing another entity in a particular subject or field of knowledge.
-
E.
languageOfSubjects
Indicates the language used by or associated with the subjects in question.
- 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 6:59 a.m.