Triple

T653181
Position Surface form Disambiguated ID Type / Status
Subject Ludwig Fischer E11387 entity
Predicate residence P75 FINISHED
Object Warsaw (during occupation) E38278 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: Warsaw (during occupation) | Statement: [Ludwig Fischer, residence, Warsaw (during occupation)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warsaw (during occupation)
Context triple: [Ludwig Fischer, residence, Warsaw (during occupation)]
  • A. Warsaw
    Warsaw is the capital and largest city of Poland, known for its resilient history, especially its near-total destruction in World War II and subsequent postwar reconstruction.
  • B. Lublin
    Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
  • C. Wilno
    Wilno is the historical Polish name for Vilnius, a major cultural and political center of the region that served as an important city in the interwar Second Polish Republic.
  • D. Warsaw District chosen
    Warsaw District was an administrative subdivision centered on Warsaw under the Nazi German General Government during World War II.
  • E. Łódź
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4a660c8190b887cb4da01ef7ae completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a4d77e0819098cdd416136fd374 completed March 3, 2026, 2:41 a.m.
Created at: March 1, 2026, 7:36 p.m.