Triple

T10197995
Position Surface form Disambiguated ID Type / Status
Subject Gerhard Gentzen E238811 entity
Predicate birthPlace P1 FINISHED
Object Greifswald E159331 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: Greifswald | Statement: [Gerhard Gentzen, birthPlace, Greifswald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greifswald
Context triple: [Gerhard Gentzen, birthPlace, Greifswald]
  • A. Greifswald chosen
    Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
  • 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. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • 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. 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.
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee3c44408190b09fa41f2d257c04 completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d74fce236481909387829c7cf311a4 completed April 9, 2026, 7:05 a.m.
Created at: March 30, 2026, 9:13 p.m.