Triple

T617811
Position Surface form Disambiguated ID Type / Status
Subject Herrenhausen Palace E14443 entity
Predicate near P350 FINISHED
Object Leine River E35561 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: Leine River | Statement: [Herrenhausen Palace, near, Leine River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leine River
Context triple: [Herrenhausen Palace, near, Leine River]
  • A. Leine chosen
    The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
  • B. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • C. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • D. Meuse
    Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
  • E. Weser
    The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e2418c881908552d2c4a5006e97 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a67eeff434819090fb550b6bf07d86 completed March 3, 2026, 6:25 a.m.
Created at: March 1, 2026, 7:35 p.m.