Triple

T10263699
Position Surface form Disambiguated ID Type / Status
Subject Johann Wigand E240663 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: [Johann Wigand, givenName, Johann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johann
Context triple: [Johann Wigand, 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d25e68fc8190b46699d2266c0505 completed April 7, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71ce5ac10819092c287bc435ae010 completed April 9, 2026, 3:28 a.m.
Created at: April 6, 2026, 11:33 a.m.