Triple

T14285316
Position Surface form Disambiguated ID Type / Status
Subject Matija E354155 entity
Predicate hasVariant P455 FINISHED
Object Matej E617373 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: Matej | Statement: [Matija, hasVariant, Matej]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matej
Context triple: [Matija, hasVariant, Matej]
  • A. Matej chosen
    Matej is a masculine given name commonly used in Slavic countries, equivalent to Matthew in English.
  • B. Matúš
    Matúš is the Slovak form of the given name Matthew, commonly used in Slovakia and other Slovak-speaking communities.
  • C. Matyáš
    Matyáš is the given name of Jindřich Matyáš Thurn, a notable Bohemian nobleman and military leader of the early 17th century.
  • D. Jozef
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • E. Marián
    Marián is a masculine given name commonly used in Slovak and other Central European cultures.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de697ef40c8190bea37724b28c2e99 completed April 14, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d1c4d988190b595e6a33ef96c28 completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:10 a.m.