Triple

T5470063
Position Surface form Disambiguated ID Type / Status
Subject Armin Hansen E122808 entity
Predicate givenName P17 FINISHED
Object Armin E412869 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: Armin | Statement: [Armin Hansen, givenName, Armin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Armin
Context triple: [Armin Hansen, givenName, Armin]
  • A. Armin chosen
    Armin is the given name of Armin Mueller-Stahl, a renowned German actor, painter, and former musician known for his work in both European and Hollywood cinema.
  • B. Reinhard
    Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
  • C. Arman
    Arman was a French-born American artist best known for his pioneering work in Nouveau Réalisme, particularly his accumulations and destructions of everyday objects as sculptural and conceptual art.
  • D. Erwin
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • E. Armandus
    Armandus is a masculine given name, a Latinized variant of Armand, historically associated with European, particularly French and Dutch, usage.
  • 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_69bd46459ff48190823377457bcf7128 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd921b65f48190af7fcf89140f9ba8 completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf6c737eb88190bcec6f257f653d32 completed March 22, 2026, 4:13 a.m.
Created at: March 20, 2026, 2:09 p.m.