Triple
T36491159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hauz Khas campus |
E899053
|
entity |
| Predicate | hasFacultyPopulation |
P52871
|
FINISHED |
| Object | hundreds of 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: hundreds of faculty members | Statement: [Hauz Khas campus, hasFacultyPopulation, hundreds of faculty members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacultyPopulation Context triple: [Hauz Khas campus, hasFacultyPopulation, hundreds of faculty members]
-
A.
hasFacultySizeApprox
chosen
Indicates that an institution has an approximate number of faculty members equal to the specified value.
-
B.
numberOfFaculties
Indicates the total count of faculties associated with a given entity.
-
C.
studentFacultyRatio
Indicates the numerical relationship between the number of students and the number of faculty members in an institution.
-
D.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
E.
academicStaffCountApprox
Indicates an approximate number of academic staff associated with an institution or organizational unit.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe6e492bf8819080b25221d13445ea |
completed | May 8, 2026, 11:14 p.m. |
| PD | Predicate disambiguation | batch_69fe6dd33a6881908fe9bbbc184cab51 |
completed | May 8, 2026, 11:12 p.m. |
Created at: May 3, 2026, 4:10 p.m.