Triple

T10728832
Position Surface form Disambiguated ID Type / Status
Subject Nordwestmecklenburg E253019 entity
Predicate contains P35 FINISHED
Object Grevesmühlen E287279 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: Grevesmühlen | Statement: [Nordwestmecklenburg, contains, Grevesmühlen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grevesmühlen
Context triple: [Nordwestmecklenburg, contains, Grevesmühlen]
  • A. Grevesmühlen chosen
    Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
  • B. Falkensee
    Falkensee is a town in the Havelland district of Brandenburg, Germany, situated just west of Berlin and functioning largely as a residential suburb of the capital.
  • C. Lippendorf
    Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
  • D. Brandenburg an der Havel
    Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
  • E. Zossen
    Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after World War II.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fc92a18819089cc67afee1c9b96 completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4416ecd748190b15f7496e1ce7728 completed April 19, 2026, 2:43 a.m.
Created at: April 8, 2026, 9:14 p.m.