Triple

T8145782
Position Surface form Disambiguated ID Type / Status
Subject Countess of Biesterfeld E190206 entity
Predicate region P40 FINISHED
Object Biesterfeld E673219 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: Biesterfeld | Statement: [Countess of Biesterfeld, region, Biesterfeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biesterfeld
Context triple: [Countess of Biesterfeld, region, Biesterfeld]
  • A. Biesterfeld chosen
    Biesterfeld was a historic estate in the Principality of Lippe that served as the ancestral seat of the Lippe-Biesterfeld noble line.
  • B. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • C. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • D. Dierdorf
    Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
  • E. Neuendorf
    Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
  • 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_69ca82be7ba8819087de0147e9292c83 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4447dbc48190affb0f34f6c85f5a completed March 31, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc94b0fc0481909a21f42364a92158 completed April 1, 2026, 3:44 a.m.
Created at: March 30, 2026, 5:36 p.m.