Triple

T437005
Position Surface form Disambiguated ID Type / Status
Subject John Warnock E10030 entity
Predicate developed P73 FINISHED
Object PDF E29775 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: PDF | Statement: [John Warnock, developed, PDF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PDF
Context triple: [John Warnock, developed, PDF]
  • A. Portable Document Format chosen
    Portable Document Format (PDF) is a widely used file format designed for reliably presenting and exchanging documents independent of software, hardware, or operating systems.
  • B. PostScript
    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.
  • C. Adobe Acrobat
    Adobe Acrobat is a widely used software application for creating, viewing, editing, and managing PDF (Portable Document Format) documents across multiple platforms.
  • D. PAPPG
    PAPPG is the National Science Foundation’s comprehensive guide outlining the policies, procedures, and requirements for preparing and managing NSF grant proposals and awards.
  • E. PEG
    PEG is the stock ticker symbol for Public Service Enterprise Group, a major U.S. energy company primarily involved in regulated electric and gas utility operations and power generation.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef0c97188190b62104cb639d4b60 completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a43e706fd8819082dd795fcad5465c completed March 1, 2026, 1:26 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.