Triple

T10542531
Position Surface form Disambiguated ID Type / Status
Subject Avenida Almirante Brown E248731 entity
Predicate locatedInCountry P40 FINISHED
Object Argentina E5383 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: Argentina | Statement: [Avenida Almirante Brown, locatedInCountry, Argentina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argentina
Context triple: [Avenida Almirante Brown, locatedInCountry, Argentina]
  • A. Argentina chosen
    Argentina is a large South American nation known for its diverse landscapes from the Andes to the Pampas, its vibrant culture including tango and football, and its capital city Buenos Aires.
  • B. Argentina and Paraguay
    Argentina and Paraguay are neighboring South American countries that share extensive cultural, historical, and economic ties along their common border.
  • C. Argentina and Chile
    Argentina and Chile are neighboring South American countries that share a long Andean border, diverse climates and landscapes, and deep historical, cultural, and economic ties.
  • D. Argentina and Bolivia
    Argentina and Bolivia are neighboring South American countries that share a long Andean and lowland frontier, including sections defined by the Bermejo River.
  • E. Argen
    Argen is a river in southern Germany that flows through the Allgäu region before emptying into Lake Constance.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5190f46d08190a92b1191881ffb92 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9342e6cf48190b0ca53ff2a4e0214 completed April 10, 2026, 5:32 p.m.
Created at: April 6, 2026, 12:32 p.m.