Triple

T8597810
Position Surface form Disambiguated ID Type / Status
Subject Beykoz E203594 entity
Predicate borders P224 FINISHED
Object Şile E191465 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: Şile | Statement: [Beykoz, borders, Şile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Şile
Context triple: [Beykoz, borders, Şile]
  • A. Şile chosen
    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.
  • B. Chile
    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.
  • C. Chileab
    Chileab is a lesser-known son of King David in the Hebrew Bible, sometimes identified with Daniel in biblical genealogies.
  • 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. 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.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46cacbe88190b95beeedc9f480b0 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc839cdc819093c3cd0e44f173a2 completed April 2, 2026, 8:07 p.m.
Created at: March 30, 2026, 6:24 p.m.