Triple

T10988337
Position Surface form Disambiguated ID Type / Status
Subject Schweinfurt (district) E259687 entity
Predicate containsRiver P165 FINISHED
Object Wern E599926 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: Wern | Statement: [Schweinfurt (district), containsRiver, Wern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wern
Context triple: [Schweinfurt (district), containsRiver, Wern]
  • A. Wern chosen
    The Wern is a river in northern Bavaria, Germany, that flows through the Schweinfurt region before joining the Main River.
  • B. Werneuchen
    Werneuchen is a small town in the German state of Brandenburg, located northeast of Berlin and characterized by its rural surroundings and commuter links to the capital.
  • C. Walheim
    Walheim is a surname most notably associated with American astronaut Rex Walheim, who flew on multiple Space Shuttle missions.
  • D. Willenberg
    Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
  • E. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b574d08190adec34b814a26437 completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e344f95ab88190bbce8f0eab0b2713 completed April 18, 2026, 8:46 a.m.
Created at: April 8, 2026, 9:24 p.m.