Triple

T9975970
Position Surface form Disambiguated ID Type / Status
Subject Duke of Bremen-Verden E196327 entity
Predicate sovereignOver P8163 FINISHED
Object Bremen-Verden E103116 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: Bremen-Verden | Statement: [Duke of Bremen-Verden, sovereignOver, Bremen-Verden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bremen-Verden
Context triple: [Duke of Bremen-Verden, sovereignOver, Bremen-Verden]
  • A. Bremen-Verden chosen
    Bremen-Verden was a former duchy in northern Germany that emerged from the secularized prince-bishoprics of Bremen and Verden and was at times ruled in personal union by Sweden.
  • B. Free City of Bremen
    The Free City of Bremen was an autonomous Hanseatic city-state in northern Germany that maintained significant commercial and political independence within various German political unions.
  • C. Dinkelscherben
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • D. Orlamünde
    Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
  • E. Stadt Norden
    Stadt Norden is the municipal government administration responsible for managing local affairs in the town of Norden in Lower Saxony, Germany.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb84b47308190aa2f94fa7320cdc3 completed April 2, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257c9f6cc81908256dc1e8d6c3fea completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:48 p.m.