Triple

T16262964
Position Surface form Disambiguated ID Type / Status
Subject Trelleborg E394800 entity
Predicate connectsByFerryTo P1831 FINISHED
Object Travemünde E332834 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: Travemünde | Statement: [Trelleborg, connectsByFerryTo, Travemünde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travemünde
Context triple: [Trelleborg, connectsByFerryTo, Travemünde]
  • A. Travemünde chosen
    Travemünde is a Baltic Sea resort town and seaside district of Lübeck in northern Germany, known for its beaches, harbor, and maritime tourism.
  • B. Bremerhaven
    Bremerhaven is a major German port city on the North Sea, known for its maritime industry, shipbuilding, and role as a key hub for trade and logistics.
  • C. Itzehoe
    Itzehoe is a historic town in northern Germany known for its medieval origins and role as a regional center in the state of Schleswig-Holstein.
  • D. Elmshorn
    Elmshorn is a town in northern Germany’s Schleswig-Holstein state, known as an industrial and commuter hub northwest of Hamburg.
  • E. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c5583c8190901e892238cf8dbd completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b5f3a8819083128cf2b90cfd84 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:04 a.m.