Triple

T12341845
Position Surface form Disambiguated ID Type / Status
Subject Konrad Zuse E294244 entity
Predicate givenName P17 FINISHED
Object Konrad E60724 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: Konrad | Statement: [Konrad Zuse, givenName, Konrad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konrad
Context triple: [Konrad Zuse, givenName, Konrad]
  • A. Konrad chosen
    Konrad is a masculine given name of German origin, historically borne by several notable figures including statesmen, nobles, and religious leaders.
  • B. Kornelius
    Kornelius is a masculine given name, commonly used in various European languages as a form of Cornelius.
  • C. Konrad Hunn
    Konrad Hunn was a medieval military leader known for his role commanding forces at the Battle of Morgarten, a key early victory for the Swiss Confederation.
  • D. Conrad the Peaceful
    Conrad the Peaceful was a 10th-century King of Burgundy who later became King of Italy and Holy Roman Emperor, noted for his relatively tranquil and conciliatory reign.
  • E. Erwin
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f7758dc8190bbc6a9ad00b01dce completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62aaa1d548190be065412aab70385 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.