Triple

T8806428
Position Surface form Disambiguated ID Type / Status
Subject Paradox E209543 entity
Predicate developer P73 FINISHED
Object Corel E552758 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: Corel | Statement: [Paradox, developer, Corel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corel
Context triple: [Paradox, developer, Corel]
  • A. Corel Centre
    Corel Centre was the original name of the multi-purpose arena in Ottawa, Ontario, that serves as the home of the NHL’s Ottawa Senators.
  • B. CorelDRAW
    CorelDRAW is a widely used vector graphics editor developed by Corel, known for its comprehensive design tools for illustration, layout, and typography.
  • C. Corel Corporation chosen
    Corel Corporation is a Canadian software company best known for products like CorelDRAW and WordPerfect.
  • D. Corel WordPerfect Office
    Corel WordPerfect Office is an office productivity suite by Corel that includes word processing, spreadsheet, presentation, and related tools, historically popular as an alternative to Microsoft Office.
  • E. Adobe Photoshop Elements
    Adobe Photoshop Elements is a simplified, consumer-oriented version of Adobe’s photo editing software designed to offer powerful yet easy-to-use tools for organizing, editing, and sharing images.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fd1f1a08190a2e584f6b0495f5c completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f96bb448190b9316ad55d61662a completed April 3, 2026, 7:43 a.m.
Created at: March 30, 2026, 6:45 p.m.