Triple

T14999294
Position Surface form Disambiguated ID Type / Status
Subject Pipile jacutinga E374040 entity
Predicate nativeTo P410 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: [Pipile jacutinga, nativeTo, Paraguay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paraguay
Context triple: [Pipile jacutinga, nativeTo, 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae048fa08190ba5719ca9868b50d completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 2:54 a.m.