Triple

T572557
Position Surface form Disambiguated ID Type / Status
Subject Potsdam E13693 entity
Predicate locatedOn P40 FINISHED
Object River Havel E30026 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: River Havel | Statement: [Potsdam, locatedOn, River Havel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Havel
Context triple: [Potsdam, locatedOn, River Havel]
  • A. River Leine
    The River Leine is a major river in central Germany that flows through the city of Hanover and several federal states before joining the Aller.
  • B. Weser
    The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
  • C. Leine
    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.
  • D. Elbe
    The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
  • E. Havel River chosen
    The Havel River is a major waterway in northeastern Germany that flows through Berlin and Brandenburg, connecting numerous lakes and serving as an important route for transport and recreation.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b49bad88190bc73d31a317c0ef4 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5291f50e481909cf404c6b4050b94 completed March 2, 2026, 6:07 a.m.
Created at: March 1, 2026, 7:33 p.m.