Triple

T6954674
Position Surface form Disambiguated ID Type / Status
Subject Mark E161211 entity
Predicate hasCognate P2525 FINISHED
Object Marko E352680 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: Marko | Statement: [Mark, hasCognate, Marko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marko
Context triple: [Mark, hasCognate, Marko]
  • A. Marko chosen
    Marko is a masculine given name, commonly used in Slavic and other European cultures, that is cognate with the name Marcus.
  • B. Marko Ramius
    Marko Ramius is a highly skilled Soviet submarine captain who masterminds a risky defection to the West in Tom Clancy’s techno-thriller "The Hunt for Red October."
  • C. Luka
    Luka is a central character in Maxim Gorky's play "The Lower Depths," known as a compassionate wanderer whose comforting lies and philosophical outlook profoundly affect the other destitute inhabitants of the shelter.
  • D. Luka
    Luka is the young protagonist of Salman Rushdie’s fantasy novel "Luka and the Fire of Life," who embarks on a magical quest to save his father.
  • E. Dragomir
    Dragomir is a Swedish actor and former criminal best known internationally for his role in the film "Easy Money" and appearances in action movies and TV series.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dace1a94819095311e4288f01784 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75883f6888190a75515be49e7879e completed March 28, 2026, 4:26 a.m.
Created at: March 27, 2026, 2:29 p.m.