Triple

T12502002
Position Surface form Disambiguated ID Type / Status
Subject Dietl E298849 entity
Predicate hasNotableBearer P458 FINISHED
Object Eduard Dietl E61874 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: Eduard Dietl | Statement: [Dietl, hasNotableBearer, Eduard Dietl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eduard Dietl
Context triple: [Dietl, hasNotableBearer, Eduard Dietl]
  • A. Eduard Dietl chosen
    Eduard Dietl was a German Wehrmacht general during World War II, noted for his leadership of mountain troops and his prominent role in early Nazi military campaigns.
  • B. Wilhelm von Leeb
    Wilhelm von Leeb was a German field marshal in the Wehrmacht during World War II, best known for leading Army Group North in the invasion of the Soviet Union.
  • C. Josef von Leeb
    Josef von Leeb was a German military officer and the son of Field Marshal Wilhelm von Leeb.
  • D. Franz Gürtner
    Franz Gürtner was a German jurist and politician who served as Minister of Justice under both the Weimar Republic and Nazi regime, playing a key role in providing legal cover for Nazi policies.
  • E. Oskar von Miller
    Oskar von Miller was a German engineer and pioneering museum founder best known for establishing Munich’s Deutsches Museum, one of the world’s leading science and technology museums.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dfbb2a48190a231b02cfa990565 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b82189081908deb76cdd4e65245 completed May 3, 2026, 12:49 a.m.
Created at: April 8, 2026, 9:57 p.m.