Triple

T1841640
Position Surface form Disambiguated ID Type / Status
Subject Tours E41188 entity
Predicate locatedOnRiver P165 FINISHED
Object Cher E36641 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: Cher | Statement: [Tours, locatedOnRiver, Cher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cher
Context triple: [Tours, locatedOnRiver, Cher]
  • A. Cher chosen
    Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
  • B. Cher
    Cher is an American singer, actress, and pop culture icon known for her distinctive contralto voice, decades-spanning career, and hits like "Believe" and "If I Could Turn Back Time."
  • C. Olivia Newton-John
    Olivia Newton-John was a British-Australian singer and actress best known for her role as Sandy in the film musical "Grease" and for hit songs such as "Physical."
  • D. Bette Midler
    Bette Midler is an American singer, actress, and comedian renowned for her powerful vocals, theatrical performances, and acclaimed work in film, television, and on stage.
  • E. La La Anthony
    La La Anthony is an American television personality and actress known for her roles in film and TV as well as her work as a host and producer.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03e7a7481909c5b902034390ef1 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9bb92a88190a00b102d3be0383c completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:33 p.m.