Triple

T15191339
Position Surface form Disambiguated ID Type / Status
Subject Vitus E363016 entity
Predicate hasVariant P455 FINISHED
Object Vít
Vít is a Czech given name derived from the Latin name Vitus, commonly used in Czech-speaking countries.
E1142012 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: Vít | Statement: [Vitus, hasVariant, Vít]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vít
Context triple: [Vitus, hasVariant, Vít]
  • A. Viotá
    Viotá is a rural municipality in the Cundinamarca department of Colombia, known for its coffee production and location in the Andean region southwest of Bogotá.
  • B. Vladimirci
    Vladimirci is a small town and municipality in western Serbia, situated in the Mačva region and known for its agricultural surroundings.
  • C. Vica
    Vica is a diminutive or nickname commonly used for the given name Ludovica.
  • D. Veleslavín
    Veleslavín is a residential district in the northwestern part of Prague known for its transport connections and proximity to green areas.
  • E. Vitryats
    Vitryats are the inhabitants or natives of the French commune of Vitry-le-François in the Marne department.
  • 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: Vít
Triple: [Vitus, hasVariant, Vít]
Generated description
Vít is a Czech given name derived from the Latin name Vitus, commonly used in Czech-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vít
Target entity description: Vít is a Czech given name derived from the Latin name Vitus, commonly used in Czech-speaking countries.
  • A. Viotá
    Viotá is a rural municipality in the Cundinamarca department of Colombia, known for its coffee production and location in the Andean region southwest of Bogotá.
  • B. Vladimirci
    Vladimirci is a small town and municipality in western Serbia, situated in the Mačva region and known for its agricultural surroundings.
  • C. Vica
    Vica is a diminutive or nickname commonly used for the given name Ludovica.
  • D. Veleslavín
    Veleslavín is a residential district in the northwestern part of Prague known for its transport connections and proximity to green areas.
  • E. Vitryats
    Vitryats are the inhabitants or natives of the French commune of Vitry-le-François in the Marne department.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067d55ac8190b7a7fce36e6ddf3c completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec8995bb08190bd7f0be0a0fcf1e7 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69feca98251081909c07f7ba4a863ad8 completed May 9, 2026, 5:48 a.m.
NED2 Entity disambiguation (via description) batch_69fecb1cc7d08190a77e8a444334b688 completed May 9, 2026, 5:50 a.m.
Created at: April 10, 2026, 3:10 a.m.