Triple
T17375205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Sévigné |
E422417
|
entity |
| Predicate | hasPreparatoryClasses |
P107673
|
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: [Collège Sévigné, hasPreparatoryClasses, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreparatoryClasses Context triple: [Collège Sévigné, hasPreparatoryClasses, true]
-
A.
hasPreparatoryDepartment
Indicates that one entity (typically an educational institution) includes or is associated with a preparatory department that provides preliminary or foundational instruction.
-
B.
hadPreparatorySchool
Indicates that an entity attended or was enrolled in a preparatory school as part of its educational background.
-
C.
hasCollegePreparatoryCurriculum
chosen
Indicates that an educational institution offers a curriculum specifically designed to prepare students for college-level study.
-
D.
hasPrePrepSchool
Indicates that an entity attended or was enrolled in a preparatory school prior to another specified educational stage or institution.
-
E.
hasGymnasium
Indicates that one entity possesses, includes, or is equipped with a gymnasium as a facility or feature.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a6c864481908507290282cc6d25 |
completed | April 19, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69e3b02ac8688190a7182f1b2151d721 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.