Triple

T2482172
Position Surface form Disambiguated ID Type / Status
Subject Duke of Brunswick-Lüneburg E55841 entity
Predicate territoryIncludes P285 FINISHED
Object Wolfenbüttel E173302 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: Wolfenbüttel | Statement: [Duke of Brunswick-Lüneburg, territoryIncludes, Wolfenbüttel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolfenbüttel
Context triple: [Duke of Brunswick-Lüneburg, territoryIncludes, Wolfenbüttel]
  • A. Wolfenbüttel chosen
    Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
  • B. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • C. Neubrandenburg
    Neubrandenburg is a historic city in northeastern Germany known for its well-preserved medieval brick Gothic architecture and distinctive city wall with multiple gate towers.
  • D. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • E. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd163378481908b75f2f5de0e89c6 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5334e25ec819090bdefaef44e849b completed March 14, 2026, 10:07 a.m.
Created at: March 6, 2026, 9:45 p.m.