Triple

T2664573
Position Surface form Disambiguated ID Type / Status
Subject John E55602 entity
Predicate hasVariant P455 FINISHED
Object János
János is the Hungarian form of the given name John, commonly used in Hungary and among Hungarian speakers.
E286726 NE FINISHED

How this triple was built (4 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: János | Statement: [John, hasVariant, János]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: János
Context triple: [John, hasVariant, János]
  • A. István
    István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
  • B. Jozef
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • C. László
    László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
  • D. Kálmán
    Kálmán is a Hungarian surname most notably associated with Rudolf E. Kálmán, the pioneering engineer and mathematician behind the Kalman filter.
  • E. András
    András is the Hungarian given name of Andrew S. Grove, the influential former CEO and co-founder of Intel.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: János
Triple: [John, hasVariant, János]
Generated description
János is the Hungarian form of the given name John, commonly used in Hungary and among Hungarian speakers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: János
Target entity description: János is the Hungarian form of the given name John, commonly used in Hungary and among Hungarian speakers.
  • A. István
    István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
  • B. Jozef
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • C. László
    László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
  • D. Kálmán
    Kálmán is a Hungarian surname most notably associated with Rudolf E. Kálmán, the pioneering engineer and mathematician behind the Kalman filter.
  • E. András
    András is the Hungarian given name of Andrew S. Grove, the influential former CEO and co-founder of Intel.
  • F. None of above. chosen

Provenance (5 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96dba44819085c3e651afba7806 completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98dc36d8819086fc739c324f0761 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af9a14cda48190bd903495ce48a4f0 completed March 10, 2026, 4:12 a.m.
NED2 Entity disambiguation (via description) batch_69af9a7b27608190ba76048c4c8a4bae completed March 10, 2026, 4:13 a.m.
Created at: March 6, 2026, 9:54 p.m.