Triple

T10215670
Position Surface form Disambiguated ID Type / Status
Subject Havelland E242434 entity
Predicate partOf P40 FINISHED
Object Federal State of Brandenburg E46660 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: Federal State of Brandenburg | Statement: [Havelland, partOf, Federal State of Brandenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Federal State of Brandenburg
Context triple: [Havelland, partOf, Federal State of Brandenburg]
  • A. Brandenburg chosen
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • B. Brandenburg
    Brandenburg is a small city in Meade County, Kentucky, situated along the Ohio River and serving as the county seat.
  • C. Mecklenburg-Vorpommern
    Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
  • D. Province of Brandenburg
    The Province of Brandenburg was a historic Prussian province in northeastern Germany that included the area around Berlin and served as a political and cultural heartland of the region.
  • E. State of Bremen
    The State of Bremen is a small federal state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port facilities.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa2894d0819095704449ecc2db6c completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87e27c2dc8190a5b3173fbcb01114 completed April 10, 2026, 4:35 a.m.
Created at: April 6, 2026, 11:05 a.m.