Triple

T5375903
Position Surface form Disambiguated ID Type / Status
Subject Route 15E E108958 entity
Predicate connects P390 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: [Route 15E, connects, Belém district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belém district
Context triple: [Route 15E, connects, 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. Morada Nova
    Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
  • D. Municipality of Belém
    The Municipality of Belém is the local government authority responsible for administering the city of Belém, the capital of the state of Pará in northern Brazil.
  • E. Botucatu
    Botucatu is a municipality in southeastern Brazil known for its higher-education institutions, especially São Paulo State University (UNESP), and its surrounding sandstone cliffs and natural landscapes.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aed2a8819089d9e699f53563db completed March 20, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf293f6458819091c32080782b56ed completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 2:03 p.m.