Triple
T5907299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maison royale de Saint-Louis |
E131370
|
entity |
| Predicate | maximumNumberOfStudents |
P53768
|
FINISHED |
| Object | 250 |
—
|
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: 250 | Statement: [Maison royale de Saint-Louis, maximumNumberOfStudents, 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfStudents Context triple: [Maison royale de Saint-Louis, maximumNumberOfStudents, 250]
-
A.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
-
B.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
C.
enrollmentSize
chosen
Indicates the number of individuals enrolled or registered in a particular group, program, or institution.
-
D.
typicalClassSize
Indicates the usual or average number of students (or participants) that are present in a single class or course section.
-
E.
hasMaximumGrade
Indicates that an entity possesses the highest possible grade or score within a defined grading or evaluation system.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.