Triple
T3542140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clifton College |
E74910
|
entity |
| Predicate | hasPrePreparatorySchool |
P45221
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Clifton College, hasPrePreparatorySchool, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrePreparatorySchool Context triple: [Clifton College, hasPrePreparatorySchool, true]
-
A.
hasPrePrepSchool
chosen
Indicates that an entity attended or was enrolled in a preparatory school prior to another specified educational stage or institution.
-
B.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
C.
hasPublicMiddleSchool
Indicates that a given area or jurisdiction contains at least one publicly funded middle school.
-
D.
hasSchoolCategory
Indicates that an entity (such as a school or educational institution) is associated with a particular category or type of school.
-
E.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with another entity.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbf73c5e881909a8352512928377b |
completed | March 8, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69adae15749881909b847c6ca73c934e |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:20 p.m.