Triple

T11534436
Position Surface form Disambiguated ID Type / Status
Subject Adolf Hurwitz E273508 entity
Predicate notableStudent P4838 FINISHED
Object Ernst Hellinger E837389 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: Ernst Hellinger | Statement: [Adolf Hurwitz, notableStudent, Ernst Hellinger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernst Hellinger
Context triple: [Adolf Hurwitz, notableStudent, Ernst Hellinger]
  • A. Ernst Hellinger chosen
    Ernst Hellinger was a German mathematician known for his contributions to functional analysis and measure theory, including work that led to the concept now called the Hellinger distance.
  • B. Hans Hahn
    Hans Hahn was an Austrian mathematician and key member of the Vienna Circle, known for his work in functional analysis and the foundations of mathematics.
  • C. Wilhelm Wirtinger
    Wilhelm Wirtinger was an Austrian mathematician known for his contributions to complex analysis, algebraic geometry, and knot theory.
  • D. Heinz Weber
    Heinz Weber is a German former professional football goalkeeper known for his career in the Bundesliga and other European leagues.
  • E. Fritz John
    Fritz John was a German-American mathematician renowned for his contributions to partial differential equations, calculus of variations, and functional analysis.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef12d90b608190b43fc3aa138aa856 completed April 27, 2026, 7:40 a.m.
Created at: April 8, 2026, 9:37 p.m.