Triple

T23171331
Position Surface form Disambiguated ID Type / Status
Subject Gusen I E578867 entity
Predicate hasSubcamp P747 FINISHED
Object Gusen III NE NERFINISHED

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: Gusen III | Statement: [Gusen I, hasSubcamp, Gusen III]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gusen III
Context triple: [Gusen I, hasSubcamp, Gusen III]
  • A. Gusen III chosen
    Gusen III was a subcamp of the Nazi Mauthausen concentration camp complex, used for forced labor under brutal conditions during World War II.
  • B. Gusen I
    Gusen I was a major Nazi concentration camp in Austria, notorious for its brutal forced labor, extremely high death rate, and role in the Mauthausen camp complex during World War II.
  • C. Gusen II
    Gusen II was a brutal Nazi concentration camp subcamp in Austria where prisoners endured extreme forced labor, starvation, and mass murder during World War II.
  • D. Guerini
    Guerini is a French surname most notably borne by Stanislas Guerini, a contemporary French politician.
  • E. Gorell
    Gorell is the middle name of Arthur John Robin Gorell Milner, a British computer scientist known for his work in process calculi and concurrency theory.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245fd2a388190b814c0dfa15f7148 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18f3007108190bc3c831f81ae1dce completed April 29, 2026, 4:55 a.m.
Created at: April 17, 2026, 4:03 p.m.