Triple

T16964060
Position Surface form Disambiguated ID Type / Status
Subject Plenary of the Congress of the Republic of Peru E411499 entity
Predicate locatedIn P40 FINISHED
Object Lima E2605 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: Lima | Statement: [Plenary of the Congress of the Republic of Peru, locatedIn, Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima
Context triple: [Plenary of the Congress of the Republic of Peru, locatedIn, Lima]
  • A. Lima chosen
    Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
  • B. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • C. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • D. Sucre
    Sucre is a coastal state in northeastern Venezuela known for its Caribbean shoreline, fishing communities, and colonial-era towns.
  • E. Sucre
    Sucre is a neighborhood or locality within the Chapinero district of Bogotá, Colombia, known primarily as a residential and commercial urban area.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0a2cda88190bd574a869f0e43e9 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d46ad58c8190be9f0b36daba8162 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.