Triple

T790217
Position Surface form Disambiguated ID Type / Status
Subject Amazon River E16895 entity
Predicate cityOnRiver P165 FINISHED
Object Belém E95648 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 | Statement: [Amazon River, cityOnRiver, Belém]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belém
Context triple: [Amazon River, cityOnRiver, Belém]
  • A. 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.
  • B. Manaus chosen
    Manaus is a major Brazilian city and capital of the state of Amazonas, known as a key gateway to the Amazon rainforest and an important industrial and cultural center in the region.
  • C. Recife
    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.
  • D. Brasília
    Brasília is the modernist-planned capital city of Brazil, known for its distinctive architecture and role as a major political and administrative center in South America.
  • E. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7841b0c8190859ecd247e32c6ec completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a79286e8b88190887def813bc65d95 completed March 4, 2026, 2:01 a.m.
Created at: March 1, 2026, 7:38 p.m.