Triple

T5301901
Position Surface form Disambiguated ID Type / Status
Subject Regency period in Brazil E120000 entity
Predicate locationOfEvent P373 FINISHED
Object Maranhão E469351 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: Maranhão | Statement: [Regency period in Brazil, locationOfEvent, Maranhão]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maranhão
Context triple: [Regency period in Brazil, locationOfEvent, Maranhão]
  • A. Maranhão chosen
    Maranhão is a northeastern Brazilian state known for its colonial heritage, Afro-Brazilian culture, and the Lençóis Maranhenses dune and lagoon landscapes.
  • B. Piauí
    Piauí is a state in northeastern Brazil known for its semi-arid landscapes, short Atlantic coastline, and rich archaeological sites such as those in Serra da Capivara National Park.
  • C. Amapá
    Amapá is a sparsely populated state in northern Brazil, located in the Amazon region along the Atlantic coast and bordering French Guiana.
  • D. Sergipe
    Sergipe is a small coastal state in northeastern Brazil known for its Atlantic shoreline, colonial history, and role in the broader Dutch and Portuguese colonial era.
  • E. Alagoas
    Alagoas is a small coastal state in northeastern Brazil known for its picturesque beaches, lagoons, and colonial-era history.
  • 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_69bd44704be88190acdb2ac481b0ff55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd851a42f08190a3017050c136b747 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21b22be08190ad5d3d6b12b80bcb completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:53 p.m.