Triple

T1222754
Position Surface form Disambiguated ID Type / Status
Subject Alagoas E26260 entity
Predicate hasCity P316 FINISHED
Object Maceió E171696 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: Maceió | Statement: [Alagoas, hasCity, Maceió]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maceió
Context triple: [Alagoas, hasCity, Maceió]
  • A. Maceió chosen
    Maceió is a coastal city in northeastern Brazil known for its white-sand beaches, turquoise waters, and vibrant tourism industry.
  • B. Aracaju
    Aracaju is a coastal city in northeastern Brazil known for its planned urban layout, beaches, and role as an administrative and economic center.
  • 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. Jaboatão dos Guararapes
    Jaboatão dos Guararapes is a major coastal city in northeastern Brazil known for its historical significance in the Dutch-Portuguese conflicts and its integration into the metropolitan area of Recife.
  • E. 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.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be21a2bc819094b47580d7c5cdf8 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad308179bc81909716b3acb9d59ea1 completed March 8, 2026, 8:17 a.m.
Created at: March 1, 2026, 7:47 p.m.