Triple
T20827778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Ward Academy |
E512748
|
entity |
| Predicate | schoolCapacity |
P117034
|
FINISHED |
| Object | approximately 1400 pupils |
—
|
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: approximately 1400 pupils | Statement: [Samuel Ward Academy, schoolCapacity, approximately 1400 pupils]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolCapacity Context triple: [Samuel Ward Academy, schoolCapacity, approximately 1400 pupils]
-
A.
hasSchoolCapacity
chosen
Indicates that an educational institution can accommodate a specified maximum number of students or occupants.
-
B.
servesStudentPopulation
Indicates that an entity provides services, resources, or support to a defined group of students.
-
C.
hasNumberOfSchools
Indicates the quantity of schools associated with a given entity.
-
D.
schoolRoll
Indicates the official list or record of students enrolled in a particular school or class.
-
E.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c31e387481909fcf323f97019803 |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:42 p.m.