Triple

T6804628
Position Surface form Disambiguated ID Type / Status
Subject John de Mol E156272 entity
Predicate givenName P17 FINISHED
Object Johannes E551148 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: Johannes | Statement: [John de Mol, givenName, Johannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johannes
Context triple: [John de Mol, givenName, Johannes]
  • A. Johannes
    Johannes is the given first name of Paul Kruger, the prominent 19th-century Boer leader and president of the South African Republic.
  • B. Johannes
    Johannes is the given first name of the German nuclear physicist Hans D. Jensen, a Nobel Prize laureate in Physics.
  • C. 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.
  • D. Johannes chosen
    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 name of Frederik Johannes Willem Reitz, a prominent South African lawyer, politician, and former State President of the Orange Free State.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2ea459c819095388218d53c250a completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723d525bc8190aaf2390d690dc6a6 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:16 p.m.