Triple
T4612768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Skull and Bones |
E100797
|
entity |
| Predicate | typicalClassSize |
P57431
|
FINISHED |
| Object | about 15 members per year |
—
|
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: about 15 members per year | Statement: [Order of Skull and Bones, typicalClassSize, about 15 members per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalClassSize Context triple: [Order of Skull and Bones, typicalClassSize, about 15 members per year]
-
A.
studentBodySize
Indicates the total number of students that make up the student body of an institution or group.
-
B.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
C.
hasFacultySizeApprox
Indicates that an institution has an approximate number of faculty members equal to the specified value.
-
D.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
E.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59c11f5481909f61e23503711cf5 |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:12 p.m.