Triple
T14801808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Calicut |
E347925
|
entity |
| Predicate | affiliatedCollegeCount |
P115773
|
FINISHED |
| Object | hundreds of affiliated colleges |
—
|
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 affiliated colleges | Statement: [University of Calicut, affiliatedCollegeCount, hundreds of affiliated colleges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affiliatedCollegeCount Context triple: [University of Calicut, affiliatedCollegeCount, hundreds of affiliated colleges]
-
A.
hasAffiliatedCollegesIn
Indicates that an institution maintains affiliated colleges located within a specified geographic area or jurisdiction.
-
B.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
-
C.
numberOfUniversities
Indicates the quantity of universities associated with a given entity.
-
D.
numberOfResidentialColleges
Indicates the quantity of residential colleges associated with a given entity.
-
E.
hasAffiliatedSchoolsIn
Indicates that an entity maintains formal affiliations or partnerships with schools located in a specified place or region.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf30d044819082ac038e06481aab |
completed | April 14, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.