Triple

T9097268
Position Surface form Disambiguated ID Type / Status
Subject KDE Applications E218058 entity
Predicate includes P1393 FINISHED
Object Okular E772960 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: Okular | Statement: [KDE Applications, includes, Okular]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Okular
Context triple: [KDE Applications, includes, Okular]
  • A. Okular document viewer chosen
    Okular document viewer is a versatile, open-source multi-format document viewer from the KDE ecosystem that supports PDFs, e-books, images, and more with advanced annotation and navigation features.
  • B. Evince
    Evince is a free, open-source document viewer for the GNOME desktop environment that supports formats like PDF, PostScript, DjVu, and TIFF.
  • C. Nepomuk
    Nepomuk is a small historic town in the Plzeň Region of the Czech Republic, best known as the birthplace of Saint John of Nepomuk.
  • D. Thunar
    Thunar is the lightweight, fast, and simple file manager designed for the Xfce desktop environment on Unix-like systems.
  • E. Konqueror file manager
    Konqueror file manager is KDE's original all-in-one file manager and web browser, known for its integration with the KDE desktop environment and versatility in handling files, web content, and network resources.
  • 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.