Triple

T706022
Position Surface form Disambiguated ID Type / Status
Subject Joachim von Ribbentrop E14100 entity
Predicate givenName P17 FINISHED
Object Joachim E69939 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: Joachim | Statement: [Joachim von Ribbentrop, givenName, Joachim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joachim
Context triple: [Joachim von Ribbentrop, givenName, Joachim]
  • A. Joachim chosen
    Joachim is a masculine given name of Hebrew origin, commonly used in German-speaking and other European countries.
  • B. Johann
    Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
  • C. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • D. Johannes
    Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
  • E. Gottfried
    Gottfried is the given name of Johann Gottfried Herder, an influential 18th-century German philosopher, theologian, and literary critic associated with the Sturm und Drang movement and early Romanticism.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a54607f08190b3ee4805f2ea4b2f completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c70997d081908a10e1aa4e936d32 completed March 4, 2026, 5:45 a.m.
Created at: March 1, 2026, 7:36 p.m.