Triple

T21946808
Position Surface form Disambiguated ID Type / Status
Subject HWI E541954 entity
Predicate appliesTo P1129 FINISHED
Object Wismar 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: Wismar | Statement: [HWI, appliesTo, Wismar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wismar
Context triple: [HWI, appliesTo, Wismar]
  • A. Wismar chosen
    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.
  • B. 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.
  • C. Lübeck
    Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • D. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • E. Güstrow
    Güstrow is a historic town in northern Germany known for its Renaissance castle, brick Gothic cathedral, and association with sculptor Ernst Barlach.
  • 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_69e0c47ef0e48190a50e1bcc43f4b3fd completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12428dee48190acb63051ed7cd03e completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:57 p.m.