Triple

T21236321
Position Surface form Disambiguated ID Type / Status
Subject Bundesautobahn 27 E523351 entity
Predicate regionServed P82 FINISHED
Object Cuxhaven district NE NERFINISHED

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: Cuxhaven district | Statement: [Bundesautobahn 27, regionServed, Cuxhaven district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuxhaven district
Context triple: [Bundesautobahn 27, regionServed, Cuxhaven district]
  • A. Cuxhaven chosen
    Cuxhaven is a German port city on the North Sea coast that historically served as an important naval and maritime hub.
  • B. Dithmarschen
    Dithmarschen is a rural district in the German state of Schleswig-Holstein, known for its North Sea coastline, marshland landscapes, and agricultural heritage.
  • C. Ostholstein
    Ostholstein is a rural district in the German state of Schleswig-Holstein, known for its Baltic Sea coastline, seaside resorts, and agricultural landscapes.
  • D. Cloppenburg
    Cloppenburg is a rural district in Lower Saxony, Germany, known for its agricultural economy and the open-air museum Museumsdorf Cloppenburg.
  • E. Pinneberg district
    Pinneberg district is an administrative district in the German state of Schleswig-Holstein, situated northwest of Hamburg and known for being one of the most densely populated rural districts in the country.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b513b89c81908b27147e91368db2 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e735202c7481909c642ddaafb40671 completed April 21, 2026, 8:28 a.m.
Created at: April 16, 2026, 3:46 p.m.