Triple

T18265871
Position Surface form Disambiguated ID Type / Status
Subject METAPOST E437480 entity
Predicate relatedTo P37 FINISHED
Object PGF/TikZ NE NERFINISHED

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: PGF/TikZ | Statement: [METAPOST, relatedTo, PGF/TikZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PGF/TikZ
Context triple: [METAPOST, relatedTo, PGF/TikZ]
  • A. TikZ chosen
    TikZ is a powerful LaTeX package for creating high-quality vector graphics and diagrams directly within TeX documents using a descriptive drawing syntax.
  • B. pgfplots
    pgfplots is a LaTeX package for creating high-quality plots and graphs based on the PGF/TikZ drawing framework.
  • C. PGF
    PGF is the IATA airport code for Perpignan–Rivesaltes Airport in southern France.
  • D. METAPOST
    METAPOST is a programming language and system for creating vector graphics, especially technical illustrations, by producing PostScript output using a syntax similar to METAFONT.
  • E. LaTeX
    LaTeX is a widely used, high-quality typesetting system particularly popular in academia for producing technical and scientific documents with precise control over layout and mathematical notation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff79851481909a4bbeb14fb00647 completed April 19, 2026, 4:14 p.m.
Created at: April 10, 2026, 10:34 a.m.