Triple

T1985999
Position Surface form Disambiguated ID Type / Status
Subject Hanseatic League E43142 entity
Predicate hasMember P10 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: [Hanseatic League, hasMember, Greifswald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greifswald
Context triple: [Hanseatic League, hasMember, 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8232d788190938f261fd4b2f2fd completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b526edc8190b4958f63268c6e97 completed March 9, 2026, 8:19 p.m.
Created at: March 4, 2026, 7:37 p.m.