Triple

T144140
Position Surface form Disambiguated ID Type / Status
Subject Johan E2916 entity
Predicate variantOf P4680 FINISHED
Object Johannes E2916 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: [Johan, variantOf, Johannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johannes
Context triple: [Johan, variantOf, Johannes]
  • A. Johan chosen
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • B. Willem
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • C. Andreas
    Andreas is a masculine given name of Greek origin, commonly used in various European and international cultures.
  • D. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • E. Johan Paul van Limburg Stirum
    Johan Paul van Limburg Stirum was a Dutch nobleman, diplomat, and colonial administrator who served as a reform-minded Governor-General in the Dutch East Indies during the early 20th century.
  • 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_69a2521e35c08190b28e5c9f1e3c9b59 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a25bab43608190ba5ebfbee6b5b6e4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a338e55004819096a8cc1bfec7a225 completed Feb. 28, 2026, 6:50 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.