Triple

T13234032
Position Surface form Disambiguated ID Type / Status
Subject Wolfgang Huber (theologian) E315095 entity
Predicate areaOfActivity P1164 FINISHED
Object 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: Brandenburg | Statement: [Wolfgang Huber (theologian), areaOfActivity, Brandenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brandenburg
Context triple: [Wolfgang Huber (theologian), areaOfActivity, 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. Saxony
    Saxony is a historic region and former kingdom in eastern Germany, known for its cultural centers like Dresden and Leipzig and its significant role in Central European history.
  • E. Weimarer Land
    Weimarer Land is a rural district in the German state of Thuringia, known for its historic towns, cultural heritage, and agricultural landscapes surrounding the city of Weimar.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d36bdf8819099949b1e0e6902d3 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716b3d28881908053df1928b18264 completed May 3, 2026, 9:34 a.m.
Created at: April 9, 2026, 9:22 p.m.