Triple

T974629
Position Surface form Disambiguated ID Type / Status
Subject Michael E21023 entity
Predicate hasVariant P455 FINISHED
Object Mikelis
Mikelis is a given name, primarily used in Latvia, that serves as a local variant of the name Michael.
 E114792 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: Mikelis | Statement: [Michael, hasVariant, Mikelis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mikelis
Context triple: [Michael, hasVariant, Mikelis]
  • A. Andris
    Andris is a masculine given name commonly used in Latvia and other Baltic and Nordic countries, equivalent to Andrew in English.
  • B. Smolikas
    Smolikas is a prominent mountain in northern Greece, known as the second-highest peak in the country after Mount Olympus.
  • C. Micali
    Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
  • D. Michal
    Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
  • E. Vasilevsky
    Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
  • 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: Mikelis
Triple: [Michael, hasVariant, Mikelis]
Generated description
Mikelis is a given name, primarily used in Latvia, that serves as a local variant of the name Michael.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mikelis
Target entity description: Mikelis is a given name, primarily used in Latvia, that serves as a local variant of the name Michael.
  • A. Andris
    Andris is a masculine given name commonly used in Latvia and other Baltic and Nordic countries, equivalent to Andrew in English.
  • B. Smolikas
    Smolikas is a prominent mountain in northern Greece, known as the second-highest peak in the country after Mount Olympus.
  • C. Micali
    Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
  • D. Michal
    Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
  • E. Vasilevsky
    Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
  • 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_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b460a5c0819087b03dfb8a3af2c2 completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac170c0fdc8190b904ca5737764f5a completed March 7, 2026, 12:16 p.m.
NEDg Description generation batch_69ac17c2e6f48190be6fce7f279957c4 completed March 7, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_69ac1844acec81909859605d2421a588 completed March 7, 2026, 12:21 p.m.
Created at: March 1, 2026, 7:40 p.m.