Triple

T8374653
Position Surface form Disambiguated ID Type / Status
Subject Saar E197544 entity
Predicate hasNameInLanguage P15 FINISHED
Object Saar (German) E729649 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: Saar (German) | Statement: [Saar, hasNameInLanguage, Saar (German)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saar (German)
Context triple: [Saar, hasNameInLanguage, Saar (German)]
  • A. Sarre (French) chosen
    Sarre is the French name for the Saar region of western Germany, historically known for its coal industry and strategic location along the French-German border.
  • B. Iller (German)
    Iller (German) is the German name for the Iller River, a tributary of the Danube in southern Germany.
  • C. Schwäbische Rezat
    The Schwäbische Rezat is a river in the German state of Bavaria that flows through the Franconian region, including the town of Weißenburg in Bayern.
  • D. 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.
  • E. Saarland
    Saarland is a small federal state in southwestern Germany known for its industrial history, Franco-German cultural influences, and location along the borders with France and Luxembourg.
  • 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_69ca82f56730819080cec5d991c76f4c completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80a996ec819083ce2607c0cdab7f completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02b4d840819090a0eaadaff9c9f9 completed April 2, 2026, 5:46 a.m.
Created at: March 30, 2026, 6:01 p.m.