Triple
T5469706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eaglebrook School |
E122799
|
entity |
| Predicate | hasStudentBodyComposition |
P5246
|
FINISHED |
| Object | all-boys |
—
|
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: all-boys | Statement: [Eaglebrook School, hasStudentBodyComposition, all-boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentBodyComposition Context triple: [Eaglebrook School, hasStudentBodyComposition, all-boys]
-
A.
hasStudentBodyType
chosen
Indicates that an educational institution possesses a student body characterized by a particular type or classification.
-
B.
hasStudentBodyFrom
Indicates that an educational institution draws or enrolls its student body from a specified geographic area, group, or source.
-
C.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
-
D.
representsStudentBody
Indicates that one entity serves as the official representative or governing body for the students of another entity (such as a school or institution).
-
E.
hasNumberOfStudentAthletes
Indicates the relationship that specifies how many student athletes are associated with a given 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.