Triple

T7393906
Position Surface form Disambiguated ID Type / Status
Subject Unix Text Processing E170572 entity
Predicate relatedTo P37 FINISHED
Object nroff E662017 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: nroff | Statement: [Unix Text Processing, relatedTo, nroff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: nroff
Context triple: [Unix Text Processing, relatedTo, nroff]
  • A. nroff chosen
    nroff is a classic Unix text-formatting program used to prepare documents for display on terminals and line printers.
  • B. troff
    troff is a classic Unix text formatting and typesetting program used to produce high-quality printed documents from plain text source files.
  • C. NRO
    NRO is the United States government agency responsible for designing, building, and operating the nation’s reconnaissance satellites and related intelligence systems.
  • D. The METAFONTbook
    The METAFONTbook is Donald Knuth’s comprehensive manual and reference guide to the METAFONT system for designing and programming digital typefaces.
  • E. 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.
  • 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_69c68a5e2c9081909e713ce866e0060a completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2263b48819089319a2a2f0d3357 completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ecf65388190a149efc77aedcd91 completed March 28, 2026, 6:32 p.m.
Created at: March 27, 2026, 3:09 p.m.