Triple

T4849242
Position Surface form Disambiguated ID Type / Status
Subject Common Market Group E108370 entity
Predicate countryServed P1083 FINISHED
Object Bolivia E3661 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: Bolivia | Statement: [Common Market Group, countryServed, Bolivia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bolivia
Context triple: [Common Market Group, countryServed, Bolivia]
  • A. Bolivia chosen
    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.
  • B. Paraguay
    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.
  • C. Peru
    Peru is a South American country known for its rich Inca heritage, diverse landscapes from Andes mountains to Amazon rainforest, and the iconic archaeological site of Machu Picchu.
  • D. Peru
    Peru is a small rural town in Berkshire County, Massachusetts, known for its elevated terrain and quiet, forested landscape in western New England.
  • 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_69bd4409b264819085ab855f3eb5381a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d1c5594819094fe021d7717032d completed March 20, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67cb1fe48190821c1daf930a70ff completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:25 p.m.