Triple
T5430636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Academy |
E121478
|
entity |
| Predicate | hasDayStudentOption |
P14073
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [King’s Academy, hasDayStudentOption, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDayStudentOption Context triple: [King’s Academy, hasDayStudentOption, yes]
-
A.
hasDayStudents
chosen
Indicates that an educational institution has students who attend during the day but do not reside on campus.
-
B.
hasStudentServices
Indicates that an entity provides or is associated with student support services for another entity or group.
-
C.
hasStudentCategory
Indicates that an entity is classified under a specific category or type of student.
-
D.
offersDaySchooling
Indicates that an entity provides daytime educational services without overnight accommodation.
-
E.
schoolDayType
Indicates the classification of a given day according to its role in the school calendar (e.g., regular school day, holiday, exam day, etc.).
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.