Triple

T4416356
Position Surface form Disambiguated ID Type / Status
Subject METAFONT E94983 entity
Predicate documentedIn P309 FINISHED
Object The METAFONTbook E437483 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: The METAFONTbook | Statement: [METAFONT, documentedIn, The METAFONTbook]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The METAFONTbook
Context triple: [METAFONT, documentedIn, The METAFONTbook]
  • A. The METAFONTbook chosen
    The METAFONTbook is Donald Knuth’s comprehensive manual and reference guide to the METAFONT system for designing and programming digital typefaces.
  • B. METAFONT
    METAFONT is a font description and rasterization system created by Donald Knuth for designing and generating bitmap fonts, particularly for use with the TeX typesetting system.
  • C. The TeXbook
    The TeXbook is Donald Knuth’s authoritative manual and tutorial on the TeX typesetting system, widely regarded as the definitive reference for learning and using TeX.
  • 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. Font’s Point
    Font’s Point is a scenic overlook in California’s Anza-Borrego Desert famed for its sweeping sunrise views over the eroded badlands.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3551afb448190a2ce2000193808ac completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b613664c548190b5cd0c2667baecc7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:29 p.m.