Triple

T16647729
Position Surface form Disambiguated ID Type / Status
Subject Karl Hajos E404515 entity
Predicate name P16 FINISHED
Object Karl Hajos E404515 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: Karl Hajos | Statement: [Karl Hajos, name, Karl Hajos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karl Hajos
Context triple: [Karl Hajos, name, Karl Hajos]
  • A. Karl Hajos chosen
    Karl Hajos was a Hungarian-American composer best known for his film scores during the early sound era of Hollywood cinema.
  • B. Alfréd Hajós
    Alfréd Hajós was a Hungarian swimmer and architect who became one of the first modern Olympic champions by winning multiple gold medals at the inaugural 1896 Games.
  • C. Karl Wien
    Karl Wien was a German mountaineer known for leading early high-altitude expeditions in Central Asia, including the pioneering ascent of Lenin Peak.
  • D. Ödön Lechner
    Ödön Lechner was a pioneering Hungarian architect often called the “Hungarian Gaudí,” renowned for fusing Art Nouveau forms with national folk motifs to create a distinctively Hungarian Secession style.
  • E. Laszlo Molnar
    Laszlo Molnar is a software developer and author known for creating the UPX (Ultimate Packer for Executables) executable compression tool.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad66fe88190be582b81719f2ac1 completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a50edea48190b65f4e6a9eb3ba24 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:18 a.m.