Triple

T23206335
Position Surface form Disambiguated ID Type / Status
Subject Anne Chapman E580466 entity
Predicate workLocation P7 FINISHED
Object Chile NE NERFINISHED

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: [Anne Chapman, workLocation, Chile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chile
Context triple: [Anne Chapman, workLocation, 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. Chilenje
    Chilenje is an alternative name for the Lenje language, a Bantu language spoken primarily in central Zambia.
  • C. 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.
  • D. 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.
  • E. Chileab
    Chileab is a lesser-known son of King David in the Hebrew Bible, sometimes identified with Daniel in biblical genealogies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24602ae1481908aaa6bc7ca493867 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1907cd62c8190afee1e963b170727 completed April 29, 2026, 5 a.m.
Created at: April 17, 2026, 4:07 p.m.