Triple

T18228959
Position Surface form Disambiguated ID Type / Status
Subject Bahrain Island E436492 entity
Predicate hasCity P316 FINISHED
Object Saar 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: Saar | Statement: [Bahrain Island, hasCity, Saar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saar
Context triple: [Bahrain Island, hasCity, Saar]
  • A. Saar chosen
    Saar is a residential town and affluent suburb in the Kingdom of Bahrain, known for its archaeological sites and proximity to the capital, Manama.
  • B. Saar
    The Saar is a river in western Europe that flows through northeastern France and western Germany, giving its name to the German state of Saarland.
  • C. Saar
    Saar was a short-lived postwar German protectorate that competed independently in international events, including the Olympics, before rejoining West Germany.
  • D. Saar River
    The Saar River is a major river in northeastern France and western Germany that flows through the industrial region of Saarland before joining the Moselle.
  • E. White Saar
    White Saar is a distinct section or branch of the Saar river system, likely named for its clearer or lighter-colored waters compared to other Saar tributaries.
  • 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f4b1b2108190a5585bbfaf2d295b completed April 19, 2026, 3:28 p.m.
Created at: April 10, 2026, 10:33 a.m.