Triple

T3636620
Position Surface form Disambiguated ID Type / Status
Subject Deutschland class E77083 entity
Predicate leadShip P44566 FINISHED
Object Deutschland 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: Deutschland | Statement: [Deutschland class, leadShip, Deutschland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deutschland
Context triple: [Deutschland class, leadShip, Deutschland]
  • A. 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.
  • B. Saksa
    Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
  • C. 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.
  • D. 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.
  • E. Germany and Austria
    Germany and Austria are neighboring Central European countries that share historical, cultural, and linguistic ties, including a common use of the German language.
  • 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3278bb8819098bbeac023410111 completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f01ef3e08190bb5ebfde40787ff2 completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:24 p.m.