Triple

T3809111
Position Surface form Disambiguated ID Type / Status
Subject Maio E93085 entity
Predicate countryCapital P204 FINISHED
Object Praia E390408 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: Praia | Statement: [Maio, countryCapital, Praia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Praia
Context triple: [Maio, countryCapital, Praia]
  • A. Praia
    Praia is the capital and largest city of Cape Verde, located on the southern coast of Santiago Island in the central Atlantic Ocean.
  • B. Praia Gonçalo chosen
    Praia Gonçalo is a small coastal village on the island of Maio in Cape Verde, known for its quiet beaches and traditional island lifestyle.
  • C. Praia Dona Ana
    Praia Dona Ana is a picturesque, cliff-backed sandy beach in the Algarve region of southern Portugal, renowned for its clear waters and dramatic rock formations.
  • D. Praia Grande
    Praia Grande is a coastal city in southeastern Brazil known for its extensive urban beaches and role as a major seaside destination in the state of São Paulo.
  • E. Praia Formosa
    Praia Formosa is a popular sandy beach on Santa Maria Island in the Azores, known for its calm waters and scenic coastal setting.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80c7fc48190b5c2400918bba5c2 completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f3590c8190b18e2e9dfd84cbcd completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:16 p.m.