Triple
T1169995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recife |
E24891
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Brejo de Beberibe
Brejo de Beberibe is a neighborhood within the city of Recife in the state of Pernambuco, Brazil.
|
E144553
|
NE FINISHED |
How this triple was built (4 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: Brejo de Beberibe | Statement: [Recife, hasPart, Brejo de Beberibe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brejo de Beberibe Context triple: [Recife, hasPart, Brejo de Beberibe]
-
A.
Brejo da Guabiraba
Brejo da Guabiraba is a neighborhood located in the northern zone of Recife, in the state of Pernambuco, Brazil.
-
B.
Caicó
Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
-
C.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
D.
Ilha Joana Bezerra
Ilha Joana Bezerra is an island neighborhood within the Brazilian city of Recife, known for its dense urban fabric and proximity to the city’s central areas.
-
E.
Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Brejo de Beberibe Triple: [Recife, hasPart, Brejo de Beberibe]
Generated description
Brejo de Beberibe is a neighborhood within the city of Recife in the state of Pernambuco, Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brejo de Beberibe Target entity description: Brejo de Beberibe is a neighborhood within the city of Recife in the state of Pernambuco, Brazil.
-
A.
Brejo da Guabiraba
Brejo da Guabiraba is a neighborhood located in the northern zone of Recife, in the state of Pernambuco, Brazil.
-
B.
Caicó
Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
-
C.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
D.
Ilha Joana Bezerra
Ilha Joana Bezerra is an island neighborhood within the Brazilian city of Recife, known for its dense urban fabric and proximity to the city’s central areas.
-
E.
Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
- F. None of above. chosen
Provenance (5 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce972cc8190bce0b77cfda6da41 |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac99730c408190a705ca67a6724778 |
completed | March 7, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69ac9a13e9548190ae1fbfeba3326cd5 |
completed | March 7, 2026, 9:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac9a96d4f081908e608a3f247bbfb2 |
completed | March 7, 2026, 9:37 p.m. |
Created at: March 1, 2026, 7:45 p.m.