Triple
T21652260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | campus of Universidade de Pernambuco in Petrolina |
E534366
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Universidade de Pernambuco |
—
|
NE NERFINISHED |
How this triple was built (3 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: Universidade de Pernambuco | Statement: [campus of Universidade de Pernambuco in Petrolina, partOf, Universidade de Pernambuco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Universidade de Pernambuco Context triple: [campus of Universidade de Pernambuco in Petrolina, partOf, Universidade de Pernambuco]
-
A.
Universidade Federal de Pernambuco
A Universidade Federal de Pernambuco is a major Brazilian public university in Recife, renowned for its strong programs in engineering, health sciences, and the humanities.
-
B.
University of Recife
The University of Recife was a Brazilian higher education institution in Pernambuco known for its role in mid-20th-century academic and intellectual life, particularly in the social and human sciences.
-
C.
Federal University of Paraíba
The Federal University of Paraíba is a major Brazilian public university known for its broad range of undergraduate and graduate programs and significant research output in the northeastern region of the country.
-
D.
Federal University of Campina Grande
The Federal University of Campina Grande is a prominent Brazilian public university known for its strong programs and research in engineering, computer science, and technology.
-
E.
Federal University of Bahia
The Federal University of Bahia is a major Brazilian public university in Salvador, Bahia, known for its strong programs in the arts, humanities, and social sciences.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Universidade de Pernambuco Target entity description: Universidade de Pernambuco is a public higher education institution in the Brazilian state of Pernambuco, offering a wide range of undergraduate and graduate programs across multiple campuses.
-
A.
Universidade Federal de Pernambuco
A Universidade Federal de Pernambuco is a major Brazilian public university in Recife, renowned for its strong programs in engineering, health sciences, and the humanities.
-
B.
University of Recife
The University of Recife was a Brazilian higher education institution in Pernambuco known for its role in mid-20th-century academic and intellectual life, particularly in the social and human sciences.
-
C.
Federal University of Paraíba
The Federal University of Paraíba is a major Brazilian public university known for its broad range of undergraduate and graduate programs and significant research output in the northeastern region of the country.
-
D.
Federal University of Campina Grande
The Federal University of Campina Grande is a prominent Brazilian public university known for its strong programs and research in engineering, computer science, and technology.
-
E.
Federal University of Bahia
The Federal University of Bahia is a major Brazilian public university in Salvador, Bahia, known for its strong programs in the arts, humanities, and social sciences.
- F. None of above. chosen
Provenance (2 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.