Triple

T10603591
Position Surface form Disambiguated ID Type / Status
Subject Usedomer Bäderbahn railway E275813 entity
Predicate hasHeadquarters P62 FINISHED
Object Heringsdorf E308284 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: Heringsdorf | Statement: [Usedomer Bäderbahn railway, hasHeadquarters, Heringsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heringsdorf
Context triple: [Usedomer Bäderbahn railway, hasHeadquarters, Heringsdorf]
  • A. Heringsdorf chosen
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • B. Hennigsdorf
    Hennigsdorf is a town in the German state of Brandenburg, located just northwest of Berlin and known for its industrial heritage and proximity to the Havel River.
  • C. Heinersdorf
    Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
  • D. Augustdorf
    Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
  • E. Hermsdorf
    Hermsdorf is a small town in the German state of Thuringia, known as an industrial and transport hub near the city of Jena.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6ded6d698819084f96f46ea941461 completed April 8, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e23b1c5e4c81909628c77b80805353 completed April 17, 2026, 1:52 p.m.
Created at: April 8, 2026, 7:32 p.m.