Triple

T7966006
Position Surface form Disambiguated ID Type / Status
Subject Bad Lausick E185206 entity
Predicate country P26 FINISHED
Object Germany 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: Germany | Statement: [Bad Lausick, country, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Germany
Context triple: [Bad Lausick, country, Germany]
  • 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. 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.
  • E. 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.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ba262208190887169fe94e47b0e completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc55dd69bc819089d280e181d43bab completed March 31, 2026, 11:16 p.m.
Created at: March 30, 2026, 5:12 p.m.