Triple

T5922539
Position Surface form Disambiguated ID Type / Status
Subject ActionScript E131731 entity
Predicate developer P73 FINISHED
Object Macromedia E30416 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: Macromedia | Statement: [ActionScript, developer, Macromedia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macromedia
Context triple: [ActionScript, developer, Macromedia]
  • A. Macromedia chosen
    Macromedia was a pioneering software company best known for creating web and multimedia tools like Flash and Dreamweaver before being acquired by Adobe.
  • B. Adobe Inc.
    Adobe Inc. is a multinational software company best known for its creative and multimedia products such as Photoshop, Illustrator, and Acrobat, widely used in digital media and design industries.
  • C. Macro Media
    Macro Media is a film and television production company known for backing culturally resonant, character-driven projects such as the 2016 drama "Fences."
  • D. Corel Corporation
    Corel Corporation is a Canadian software company best known for products like CorelDRAW and WordPerfect.
  • E. Flash (software)
    Flash (software) is a now-discontinued multimedia platform used for creating and displaying interactive web content, animations, and browser-based games and applications.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03804d9808190829a418adb7864aa completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c041d4f08190863141b037b1c05f completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 4 p.m.