Triple

T1647935
Position Surface form Disambiguated ID Type / Status
Subject VBA E35623 entity
Predicate runsInside P23495 FINISHED
Object Microsoft Word E56704 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: Microsoft Word | Statement: [VBA, runsInside, Microsoft Word]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft Word
Context triple: [VBA, runsInside, Microsoft Word]
  • A. Word chosen
    Word is Microsoft’s widely used word processing application for creating, editing, and formatting text documents.
  • B. Adobe Acrobat
    Adobe Acrobat is a widely used software application for creating, viewing, editing, and managing PDF (Portable Document Format) documents across multiple platforms.
  • C. Microsoft 365
    Microsoft 365 is a subscription-based suite of productivity and collaboration tools that combines Office applications with cloud services, security features, and device management.
  • D. MacWrite
    MacWrite was one of the first WYSIWYG word processors for the original Macintosh, showcasing the platform’s graphical user interface and desktop publishing capabilities.
  • E. PowerPoint
    PowerPoint is a widely used Microsoft presentation software application for creating, editing, and delivering slide-based visual presentations.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61e142ac8190aa2fbd8f0826b5b2 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a73a288190a659e2a1f09ba524 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:29 p.m.