Triple

T22087631
Position Surface form Disambiguated ID Type / Status
Subject Erwin von Witzleben E545824 entity
Predicate givenName P17 FINISHED
Object Erwin 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: Erwin | Statement: [Erwin von Witzleben, givenName, Erwin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erwin
Context triple: [Erwin von Witzleben, givenName, Erwin]
  • A. Erwin chosen
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • B. Benno
    Benno is a masculine given name, used as a variant or extended form of the name Ben in various European languages.
  • C. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • D. Günther
    Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
  • E. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e3a98481908a7b3dc3f2a90276 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.