Triple
T17610882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Baccalaureate Career-related Programme |
E428960
|
entity |
| Predicate | subjectAreaExamples |
P28568
|
FINISHED |
| Object | business |
—
|
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: business | Statement: [International Baccalaureate Career-related Programme, subjectAreaExamples, business]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAreaExamples Context triple: [International Baccalaureate Career-related Programme, subjectAreaExamples, business]
-
A.
subjectAreaLevel
Indicates the hierarchical level or depth of specialization of a particular subject area in relation to others.
-
B.
thematicArea
chosen
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
-
C.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
D.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
E.
regionOfAcademicInterest
Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.