Triple

T14248661
Position Surface form Disambiguated ID Type / Status
Subject OAS member states E353198 entity
Predicate includes P1393 FINISHED
Object Paraguay E28339 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: Paraguay | Statement: [OAS member states, includes, Paraguay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paraguay
Context triple: [OAS member states, includes, Paraguay]
  • A. Paraguay chosen
    Paraguay is a landlocked country in central South America known for its bilingual Spanish and Guaraní culture and its location along the Paraguay and Paraná rivers.
  • 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. Uruguay
    Uruguay is a small South American country known for its stable democracy, high standard of living, and Atlantic coastline between Brazil and Argentina.
  • D. PARAGUAYA
    PARAGUAYA is the radio callsign used by LATAM Airlines Paraguay for air traffic control and communication purposes.
  • E. Bolivia
    Bolivia is a landlocked country in central South America known for its diverse indigenous cultures, Andean and Amazonian landscapes, and administrative capitals La Paz and Sucre.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6295ef9081909cfb0c1283bca21a completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46794e9c819093312a2c304e554e completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:08 a.m.