Triple

T10127687
Position Surface form Disambiguated ID Type / Status
Subject 게르하르트 슈뢰더 E226255 entity
Predicate 국적 P78054 FINISHED
Object 독일 E1728 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: 독일 | Statement: [게르하르트 슈뢰더, 국적, 독일]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 독일
Context triple: [게르하르트 슈뢰더, 국적, 독일]
  • A. Saksa
    Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
  • B. Germany chosen
    Germany is a major Central European country known for its pivotal role in 20th-century history, its strong industrial economy, and its influential contributions to science, philosophy, music, and engineering.
  • C. Germania
    Germania was the ancient Roman term for the vast region of central Europe inhabited by various Germanic tribes beyond the empire’s northeastern frontiers.
  • D. Francen
    Francen is a surname most notably associated with Victor Francen, a Belgian-born actor prominent in early 20th-century European and American cinema.
  • E. West Germany
    West Germany was the democratic, capitalist western portion of Germany during the Cold War, which became an economic powerhouse and key NATO member after World War II.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd2f0a0e881909267a83fbeb31f0c completed April 2, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d32aa5032081909b2aab2f8eb4c4a7 completed April 6, 2026, 3:38 a.m.
Created at: March 30, 2026, 9:05 p.m.