Triple

T13875523
Position Surface form Disambiguated ID Type / Status
Subject River Parthe E333571 entity
Predicate mouthOf P1008 FINISHED
Object White Elster E119578 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: White Elster | Statement: [River Parthe, mouthOf, White Elster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: White Elster
Context triple: [River Parthe, mouthOf, White Elster]
  • A. White Elster chosen
    White Elster is a river in central Europe that flows through parts of Germany, including the city of Gera, before joining the Saale River.
  • B. Hufstedler
    Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
  • C. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • D. Estermann
    Estermann is a surname most notably associated with mathematician Theodor Estermann, known for his contributions to analytic number theory.
  • E. Loerzer
    Loerzer is the surname of Bruno Loerzer, a notable German First World War flying ace and later Luftwaffe general.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be556708190bbcf0b3583f677e3 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c109ac5c819090b2b7e43334f904 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:15 p.m.