Triple

T6491536
Position Surface form Disambiguated ID Type / Status
Subject Lippe E148047 entity
Predicate sourceCountry 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: [Lippe, sourceCountry, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Germany
Context triple: [Lippe, sourceCountry, 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9bf9208190b0957eda06ed3d65 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c669d6ff748190b77d5a2c9cbe506b completed March 27, 2026, 11:28 a.m.
Created at: March 22, 2026, 4:53 p.m.