Triple

T2813087
Position Surface form Disambiguated ID Type / Status
Subject MV E54217 entity
Predicate associatedWithCapital P24465 FINISHED
Object Schwerin E138060 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: Schwerin | Statement: [MV, associatedWithCapital, Schwerin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwerin
Context triple: [MV, associatedWithCapital, Schwerin]
  • A. Schwerin chosen
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • B. Neubrandenburg
    Neubrandenburg is a historic city in northeastern Germany known for its well-preserved medieval brick Gothic architecture and distinctive city wall with multiple gate towers.
  • C. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • D. 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.
  • E. 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.
  • 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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde4a31d081909377044d5ff791b0 completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4c358374c819089e8c16d4115c409 completed March 14, 2026, 2:09 a.m.
Created at: March 6, 2026, 9:59 p.m.