Triple
T25230753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APJ Abdul Kalam Technological University |
E632212
|
entity |
| Predicate | hasAffiliatedInstitutionsType |
P29027
|
FINISHED |
| Object | management institutions |
—
|
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: management institutions | Statement: [APJ Abdul Kalam Technological University, hasAffiliatedInstitutionsType, management institutions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAffiliatedInstitutionsType Context triple: [APJ Abdul Kalam Technological University, hasAffiliatedInstitutionsType, management institutions]
-
A.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
B.
associatedInstitutionType
chosen
Indicates the type or category of institution with which an entity is associated.
-
C.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with a particular institution.
-
D.
hasAffiliatedSchoolsIn
Indicates that an entity maintains formal affiliations or partnerships with schools located in a specified place or region.
-
E.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 21, 2026, 1:04 p.m.