Triple

T6908780
Position Surface form Disambiguated ID Type / Status
Subject Aurich district E159878 entity
Predicate hasBorderWith P224 FINISHED
Object Emden E29348 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: Emden | Statement: [Aurich district, hasBorderWith, Emden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emden
Context triple: [Aurich district, hasBorderWith, Emden]
  • A. Emden chosen
    Emden is a historic port city in northwestern Germany known for its maritime industry and location near the North Sea.
  • B. Dukenburg
    Dukenburg is a residential district in the southwest of Nijmegen in the Netherlands, known for its post-war urban planning and local railway connectivity.
  • C. Marienwerder
    Marienwerder is a historic town in former West Prussia, now known as Kwidzyn in Poland, noted for its medieval architecture and Teutonic Order castle.
  • D. Cattaro
    Cattaro is the historical Italian name for the coastal town of Kotor in Montenegro, known for its well-preserved medieval old town and bay.
  • E. Kolberg
    Kolberg is a historic Baltic Sea port city in present-day Kołobrzeg, Poland, known for its strategic military importance and spa tourism.
  • 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_69c68839ccb88190b4aa5cc1aca3448f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9be98748190b5cb698e66e3aa42 completed March 27, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7882712548190a0c7e5660c61625d completed March 28, 2026, 7:49 a.m.
Created at: March 27, 2026, 2:25 p.m.