Triple

T6537437
Position Surface form Disambiguated ID Type / Status
Subject Franz von Papen E168199 entity
Predicate placeOfBirth P1 FINISHED
Object Werl E100762 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: Werl | Statement: [Franz von Papen, placeOfBirth, Werl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Werl
Context triple: [Franz von Papen, placeOfBirth, Werl]
  • A. Werl chosen
    Werl is a town in North Rhine-Westphalia, Germany, known for its historical significance and regional correctional facility.
  • B. Stadshagen
    Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • C. Bentheim
    Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
  • D. Lüdenscheid
    Lüdenscheid is a town in western Germany’s Sauerland region, historically noted for its role in World War II and known today for its metal and plastics industries.
  • E. Rudolfswerth
    Rudolfswerth is the former German name for Novo Mesto, a historic town in southeastern Slovenia known for its medieval heritage and role as a regional cultural center.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6add33acc8190bb0a9531648198f2 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d53616848190835d9f02bd8e2dbf completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:49 p.m.