Triple

T12562042
Position Surface form Disambiguated ID Type / Status
Subject XeTeX E295373 entity
Predicate compatibleWith P203 FINISHED
Object plain TeX E621159 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: plain TeX | Statement: [XeTeX, compatibleWith, plain TeX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: plain TeX
Context triple: [XeTeX, compatibleWith, plain TeX]
  • A. plain TeX chosen
    plain TeX is Donald Knuth’s original, low-level typesetting system that provides a minimal, macro-based foundation for creating structured documents and is often used as a base for higher-level formats like LaTeX.
  • B. 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.
  • C. 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.
  • D. upTeX
    upTeX is a Japanese-enabled TeX engine that extends pTeX with full Unicode support for typesetting multilingual documents, especially those containing Japanese text.
  • E. XeTeX
    XeTeX is an extension of the TeX typesetting system that natively supports Unicode and modern font technologies like OpenType, enabling high-quality multilingual and typographically advanced document production.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95494ae1c81908b9ee14b8ef92a65 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6558da7e0819086860bfaf394e2d8 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:48 p.m.