Triple
T30694538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Page Corps |
E781419
|
entity |
| Predicate | hadPreparatoryClass |
P170042
|
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: [Page Corps, hadPreparatoryClass, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPreparatoryClass Context triple: [Page Corps, hadPreparatoryClass, yes]
-
A.
hadPreparatorySchool
Indicates that an entity attended or was enrolled in a preparatory school as part of its educational background.
-
B.
hasPrePrepSchool
Indicates that an entity attended or was enrolled in a preparatory school prior to another specified educational stage or institution.
-
C.
hasPreparatoryDepartment
Indicates that one entity (typically an educational institution) includes or is associated with a preparatory department that provides preliminary or foundational instruction.
-
D.
hasCollegePreparatoryCurriculum
Indicates that an educational institution offers a curriculum specifically designed to prepare students for college-level study.
-
E.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
- F. None of above. chosen
Provenance (4 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_69f224ab24e08190991d6edb6df58e8b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68bda88048190bdd6992094c7644d |
completed | May 2, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 29, 2026, 8:33 p.m.