Triple

T5901717
Position Surface form Disambiguated ID Type / Status
Subject Georg Elser E131241 entity
Predicate givenName P17 FINISHED
Object Johann E27352 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: Johann | Statement: [Georg Elser, givenName, Johann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johann
Context triple: [Georg Elser, givenName, Johann]
  • A. Johann chosen
    Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
  • B. Johannes
    Johannes is the given first name of Hubertus van Mook, a Dutch colonial administrator who served as Governor-General of the Dutch East Indies during and after World War II.
  • C. Johannes
    Johannes is the given first name of the German nuclear physicist Hans D. Jensen, a Nobel Prize laureate in Physics.
  • D. Johannes
    Johannes is a masculine given name of Hebrew origin, related to names like John and Johan and common in various European languages.
  • E. Johannes
    Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
  • 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_69c0085864a88190a569c05ff7d65f29 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0373489208190ba51c013e81c9938 completed March 22, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cbc676c8190bdac874391a608e8 completed March 23, 2026, 10:58 a.m.
Created at: March 22, 2026, 3:58 p.m.