Triple

T16870006
Position Surface form Disambiguated ID Type / Status
Subject Yohanan E410143 entity
Predicate hasRelatedName P3889 FINISHED
Object Johanan 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: Johanan | Statement: [Yohanan, hasRelatedName, Johanan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johanan
Context triple: [Yohanan, hasRelatedName, Johanan]
  • A. Johan
    Johan is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • B. Johan
    Johan is the given first name of the Swedish playwright and novelist August Strindberg.
  • C. Johan
    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.
  • 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 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.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b50b85c08190b35d1c45ee0e9675 completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfc531c881908a33de8b491842ca completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:24 a.m.