Triple
T2841636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doshisha University |
E62482
|
entity |
| Predicate | facultyMembersApprox |
P26574
|
FINISHED |
| Object | over 1,000 |
—
|
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: over 1,000 | Statement: [Doshisha University, facultyMembersApprox, over 1,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facultyMembersApprox Context triple: [Doshisha University, facultyMembersApprox, over 1,000]
-
A.
academicStaffCountApprox
chosen
Indicates an approximate number of academic staff associated with an institution or organizational unit.
-
B.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
-
C.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
D.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
E.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf16d0c08190bb8de4a4160b4414 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.