Triple
T4077337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INSEAD |
E87394
|
entity |
| Predicate | hasFacultySizeApprox |
P52871
|
FINISHED |
| Object | over 150 faculty members |
—
|
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 150 faculty members | Statement: [INSEAD, hasFacultySizeApprox, over 150 faculty members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacultySizeApprox Context triple: [INSEAD, hasFacultySizeApprox, over 150 faculty members]
-
A.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
C.
numberOfFaculties
Indicates the total count of faculties associated with a given entity.
-
D.
studentFacultyRatio
Indicates the numerical relationship between the number of students and the number of faculty members in an institution.
-
E.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc4d348c8190a94724639830aca0 |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.