Triple
T18849046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida da Índia |
E460991
|
entity |
| Predicate | connectsArea |
P2564
|
FINISHED |
| Object | Belém district |
E18930
|
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: Belém district | Statement: [Avenida da Índia, connectsArea, Belém district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belém district Context triple: [Avenida da Índia, connectsArea, Belém district]
-
A.
Belém do Pará
Belém do Pará is a major port city in northern Brazil, known as the gateway to the Amazon region and an important cultural and economic center.
-
B.
Belém
chosen
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.
-
C.
Ponto District
Ponto District is an administrative district located within Huari Province in the Ancash Region of Peru.
-
D.
Feira de Santana
Feira de Santana is a major commercial and transportation hub in northeastern Brazil and the second-largest city in the state of Bahia.
-
E.
Morada Nova
Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8f1abdc819081638ed384da191e |
completed | April 20, 2026, 5:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0575b1b26c8190ac2fbf2615f7f0e0 |
completed | May 14, 2026, 7:11 a.m. |
Created at: April 10, 2026, 11:56 a.m.