Triple

T21995449
Position Surface form Disambiguated ID Type / Status
Subject Gianni E543193 entity
Predicate etymologicalRoot P453 FINISHED
Object Iohannes 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: Iohannes | Statement: [Gianni, etymologicalRoot, Iohannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iohannes
Context triple: [Gianni, etymologicalRoot, Iohannes]
  • A. Johannes chosen
    Johannes is a masculine given name of Hebrew origin, related to names like John and Johan and common in various European languages.
  • 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 name of Frederik Johannes Willem Reitz, a prominent South African lawyer, politician, and former State President of the Orange Free State.
  • D. Johannes
    Johannes is the given first name of the German nuclear physicist Hans D. Jensen, a Nobel Prize laureate in Physics.
  • 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 (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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276493bc81908567445e901bc3a7 completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:19 p.m.