Triple

T2889441
Position Surface form Disambiguated ID Type / Status
Subject TECO Emacs E59583 entity
Predicate influenced P9 FINISHED
Object GNU Emacs E9097 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: GNU Emacs | Statement: [TECO Emacs, influenced, GNU Emacs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GNU Emacs
Context triple: [TECO Emacs, influenced, GNU Emacs]
  • A. GNU Emacs chosen
    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.
  • B. XEmacs
    XEmacs is a highly customizable, extensible text editor and development environment that forked from GNU Emacs and evolved with its own features, interface enhancements, and community.
  • C. TECO Emacs
    TECO Emacs is an early, TECO-based text editor that served as a direct precursor and foundational influence to modern Emacs implementations like GNU Emacs.
  • D. Emacs Lisp (for GNU Emacs environment)
    Emacs Lisp is a dialect of the Lisp programming language used as the extension and scripting language of the GNU Emacs text editor.
  • E. Gnus
    Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04a68ac8190aaeafe52138beb74 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03179d7448190bcdbea164856aaa2 completed March 10, 2026, 2:58 p.m.
Created at: March 6, 2026, 10:04 p.m.