Triple

T21940433
Position Surface form Disambiguated ID Type / Status
Subject Terra do Sal E541803 entity
Predicate appliesTo P1129 FINISHED
Object Mossoró NE NERFINISHED

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: Mossoró | Statement: [Terra do Sal, appliesTo, Mossoró]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mossoró
Context triple: [Terra do Sal, appliesTo, Mossoró]
  • A. Mossoró chosen
    Mossoró is a major city in northeastern Brazil known for its oil industry, salt production, and strong cultural traditions in the state of Rio Grande do Norte.
  • B. Cumbuco
    Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
  • C. Macaé
    Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
  • D. Barra do Corda
    Barra do Corda is a municipality in the Brazilian state of Maranhão, known for its location in the interior region and its role as a local commercial and cultural center.
  • E. Itanhaém
    Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12420b1cc81909b375891aedc0979 completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:55 p.m.