Triple

T10835192
Position Surface form Disambiguated ID Type / Status
Subject River Pleiße E255735 entity
Predicate mouthRiver P4359 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 Pleiße, mouthRiver, White Elster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: White Elster
Context triple: [River Pleiße, mouthRiver, 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d746fdefd4819099772efbd4f302cb completed April 9, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7c739708190b0d58fc2d6392c6c completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:19 p.m.