Triple

T12749637
Position Surface form Disambiguated ID Type / Status
Subject Hanse Sail E304695 entity
Predicate mainVenue P373 FINISHED
Object Warnemünde E330763 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: Warnemünde | Statement: [Hanse Sail, mainVenue, Warnemünde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warnemünde
Context triple: [Hanse Sail, mainVenue, Warnemünde]
  • A. Warnemünde chosen
    Warnemünde is a seaside district and popular Baltic Sea resort of the German city of Rostock, known for its wide sandy beaches and maritime atmosphere.
  • B. Ostseebad
    Ostseebad is a German designation for a seaside resort town on the Baltic Sea, recognized for its coastal tourism and spa facilities.
  • C. Rostock
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • D. Stralsund
    Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
  • E. Bandorf
    Bandorf is a small district of the town of Remagen in the Rhineland-Palatinate region of western Germany.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd75f508190aaae0969f33d1523 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f746077b288190b8ca7927352a7904 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 5:27 p.m.