Triple
T5510614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brejo de Beberibe |
E144553
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Recife |
E24891
|
NE 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: Recife | Statement: [Brejo de Beberibe, partOf, Recife]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Recife Context triple: [Brejo de Beberibe, partOf, Recife]
-
A.
Recife
chosen
Recife is a major coastal city in northeastern Brazil known for its historic colonial architecture, extensive waterways, and role as an important cultural and economic center.
-
B.
Aracaju
Aracaju is a coastal city in northeastern Brazil known for its planned urban layout, beaches, and role as an administrative and economic center.
-
C.
Jaboatão dos Guararapes
Jaboatão dos Guararapes is a major coastal city in northeastern Brazil known for its historical significance in the Dutch-Portuguese conflicts and its integration into the metropolitan area of Recife.
-
D.
Maceió
Maceió is a coastal city in northeastern Brazil known for its white-sand beaches, turquoise waters, and vibrant tourism industry.
-
E.
Belém
Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f4cbc2c819091fcbff5f39ceeb4 |
completed | March 22, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d567cb48190839f340041f2300b |
completed | March 22, 2026, 11:37 p.m. |
Created at: March 22, 2026, 3:33 p.m.