Triple
T3054860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Milan |
E60455
|
entity |
| Predicate | publicUniversity |
P35654
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [University of Milan, publicUniversity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicUniversity Context triple: [University of Milan, publicUniversity, true]
-
A.
publicUniversityType
chosen
Indicates that an institution is classified as a public university, typically funded and operated by government or state authorities.
-
B.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
-
C.
university2
Indicates a relationship where an entity is a university associated with, attended by, or otherwise linked to another entity.
-
D.
stateUniversity
Indicates that an institution is a university that is publicly funded and operated under the authority of a state or similar governmental entity.
-
E.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf6b9948190bc957bfd1579c471 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.