Triple
T1436331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Calcutta |
E30568
|
entity |
| Predicate | affiliatedCollegesCount |
P6738
|
FINISHED |
| Object | hundreds |
—
|
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 | Statement: [University of Calcutta, affiliatedCollegesCount, hundreds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affiliatedCollegesCount Context triple: [University of Calcutta, affiliatedCollegesCount, hundreds]
-
A.
isConstituentCollegeOf
Indicates that one educational institution functions as a constituent or affiliated college that forms part of a larger parent university or institution.
-
B.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
-
C.
numberOfFaculties
Indicates the total count of faculties associated with a given entity.
-
D.
numberOfColleges
chosen
Indicates the quantity of colleges associated with a given entity.
-
E.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.