Triple

T7033163
Position Surface form Disambiguated ID Type / Status
Subject AI (file format) E163316 entity
Predicate basedOn P98 FINISHED
Object PostScript E30048 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: PostScript | Statement: [AI (file format), basedOn, PostScript]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostScript
Context triple: [AI (file format), basedOn, PostScript]
  • A. PostScript chosen
    PostScript is a page description and programming language widely used in desktop publishing and printing to precisely define the layout and appearance of text and graphics.
  • B. PasteScript
    PasteScript is a Python-based command-line tool that streamlines creating, managing, and deploying web application projects through reusable templates and scripts.
  • C. Ghostscript
    Ghostscript is a suite of software that interprets and renders PostScript and PDF files, widely used for document viewing, printing, and conversion.
  • D. Postscript-1969
    Postscript-1969 is Thomas S. Kuhn’s later-added reflective essay to *The Structure of Scientific Revolutions*, in which he clarifies and refines key concepts such as paradigms and incommensurability in response to critics.
  • E. Adobe PageMaker
    Adobe PageMaker was one of the first widely used desktop publishing applications, popular in the 1980s and 1990s for creating professional-quality printed documents such as brochures, newsletters, and books.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e2118fc88190a0751ca18eafb4a5 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7759c8e408190a7d457e77a44ee26 completed March 28, 2026, 6:30 a.m.
Created at: March 27, 2026, 2:36 p.m.