Triple

T13776180
Position Surface form Disambiguated ID Type / Status
Subject Johannes Hendrik Voskuijl E331012 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: [Johannes Hendrik Voskuijl, givenName, Johannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johannes
Context triple: [Johannes Hendrik Voskuijl, 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
    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.
  • E. Johannes chosen
    Johannes is a masculine given name of Hebrew origin, related to names like John and Johan and common in various European languages.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0238bdbc8190a946e6e5431632a5 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a86c9ff88190a2e4f6aa907f2eba completed May 3, 2026, 7:56 p.m.
Created at: April 9, 2026, 10:10 p.m.