Triple

T7785754
Position Surface form Disambiguated ID Type / Status
Subject Rubén E187239 entity
Predicate commonInCountry P7827 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: [Rubén, commonInCountry, Chile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chile
Context triple: [Rubén, commonInCountry, 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 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. Chileab
    Chileab is a lesser-known son of King David in the Hebrew Bible, sometimes identified with Daniel in biblical genealogies.
  • E. 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.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cadf22d9b4819081b877c751204a22 completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf5f4fa6c8190a85ba9019c0e5345 completed March 30, 2026, 10:15 p.m.
Created at: March 30, 2026, 4:23 p.m.