Triple

T477697
Position Surface form Disambiguated ID Type / Status
Subject GNU Emacs E9097 entity
Predicate programmingLanguage P1592 FINISHED
Object Emacs Lisp E12505 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: Emacs Lisp | Statement: [GNU Emacs, programmingLanguage, Emacs Lisp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emacs Lisp
Context triple: [GNU Emacs, programmingLanguage, Emacs Lisp]
  • A. Emacs Lisp (for GNU Emacs environment) chosen
    Emacs Lisp is a dialect of the Lisp programming language used as the extension and scripting language of the GNU Emacs text editor.
  • B. GNU Emacs
    GNU Emacs is a highly extensible, customizable text editor and computing environment that serves as a flagship project of the GNU system and the free software movement.
  • C. Scheme
    Scheme is a minimalist, lexically scoped dialect of the Lisp programming language known for its elegant functional programming model and powerful macro system.
  • D. Elm
    Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
  • E. Elm
    Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f03f3fbc81909af6e4496d5e6c2a completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a46804b90881908422851eeb9bbba1 completed March 1, 2026, 4:23 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.