Triple

T1972103
Position Surface form Disambiguated ID Type / Status
Subject Josef Albers E42823 entity
Predicate givenName P17 FINISHED
Object Josef E66212 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: Josef | Statement: [Josef Albers, givenName, Josef]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Josef
Context triple: [Josef Albers, givenName, Josef]
  • A. Jozef chosen
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • B. Josef Jennewein
    Josef Jennewein was a German World War II Luftwaffe fighter ace and former Olympic alpine skier.
  • C. Franz
    Franz is the given name of Franz Cardinal König, a prominent 20th-century Austrian Catholic cardinal and influential church leader.
  • D. Josef Naus
    Josef Naus was a 19th-century Bavarian surveyor and mountaineer best known for leading the first recorded ascent of Germany’s highest peak, the Zugspitze.
  • E. Eduard
    Eduard is a central character in Paulo Coelho’s novel "Veronika Decides to Die," portrayed as a sensitive, introspective young man whose relationship with the protagonist profoundly influences her view of life and death.
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3f275408190affa93f8cb6a8184 completed March 7, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3abc8cc819086e7b640d5231641 completed March 9, 2026, 11:48 a.m.
Created at: March 4, 2026, 7:36 p.m.