Triple

T4965027
Position Surface form Disambiguated ID Type / Status
Subject Calafquén Lake E111502 entity
Predicate basinCountry P411 FINISHED
Object Chile E203 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: Chile | Statement: [Calafquén Lake, basinCountry, Chile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chile
Context triple: [Calafquén Lake, basinCountry, Chile]
  • A. Chile chosen
    Chile is a long, narrow South American country stretching along the Pacific coast, renowned for its diverse climates, stable economy, and world-class astronomical observatories.
  • B. Şile
    Şile is a coastal district on the Black Sea known for its beaches, lighthouse, and traditional Şile cloth, located on the Asian side of Istanbul, Turkey.
  • C. Argentina
    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.
  • D. 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.
  • E. Peru
    Peru is a small rural town in Berkshire County, Massachusetts, known for its elevated terrain and quiet, forested landscape in western New England.
  • 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71f693b48190b3523cd314303cbe completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81f13988819097dcd5a65cb1f502 completed March 21, 2026, 11:33 a.m.
Created at: March 20, 2026, 1:32 p.m.