Triple

T7504648
Position Surface form Disambiguated ID Type / Status
Subject Foyn Coast E177355 entity
Predicate countryClaimedBy P8163 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: [Foyn Coast, countryClaimedBy, Argentina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argentina
Context triple: [Foyn Coast, countryClaimedBy, 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. Argen
    Argen is a river in southern Germany that flows through the Allgäu region before emptying into Lake Constance.
  • E. Uruguay
    Uruguay is a small South American country known for its stable democracy, high standard of living, and Atlantic coastline between Brazil and Argentina.
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5b4c83c8190ace59f4d9e271904 completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ef2e4588190bedda247ed83bd88 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:44 p.m.