Triple
T34854277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adesh University |
E1004683
|
entity |
| Predicate | hasAffiliatedCollegeType |
P69155
|
FINISHED |
| Object | Medical college |
—
|
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: Medical college | Statement: [Adesh University, hasAffiliatedCollegeType, Medical college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAffiliatedCollegeType Context triple: [Adesh University, hasAffiliatedCollegeType, Medical college]
-
A.
hasCollegesType
chosen
Indicates that an entity is associated with or classified by a particular type or category of college.
-
B.
hasAffiliatedCollegesIn
Indicates that an institution maintains affiliated colleges located within a specified geographic area or jurisdiction.
-
C.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
hasCollegeType
Indicates that a college or educational institution is classified as having a specific type or category (e.g., public, private, community, technical).
-
E.
hasAffiliatedSchoolsIn
Indicates that an entity maintains formal affiliations or partnerships with schools located in a specified place or region.
- 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.