Triple

T9097273
Position Surface form Disambiguated ID Type / Status
Subject KDE Applications E218058 entity
Predicate includes P1393 FINISHED
Object Kdenlive E772964 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: Kdenlive | Statement: [KDE Applications, includes, Kdenlive]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kdenlive
Context triple: [KDE Applications, includes, Kdenlive]
  • A. Kdenlive video editor chosen
    Kdenlive video editor is a free, open-source non-linear video editing application known for its powerful features and integration within the KDE software ecosystem.
  • B. DaVinci Resolve
    DaVinci Resolve is a professional video editing, color grading, visual effects, and audio post-production software suite widely used in film and television.
  • C. Lightworks
    Lightworks is a track by the experimental hip-hop producer Donuts, known for its intricate sampling and innovative beat construction.
  • D. Cutcut
    Cutcut is a barangay (village-level administrative division) located in Angeles City in the province of Pampanga, Philippines.
  • E. Adobe Premiere Pro
    Adobe Premiere Pro is a professional non-linear video editing software widely used in film, television, and online content production.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b7d0d48190a3b15f35bef087e3 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0181a9ae88190ab80d4e80e919f42 completed April 3, 2026, 7:42 p.m.
Created at: March 30, 2026, 7:15 p.m.