Triple

T8828451
Position Surface form Disambiguated ID Type / Status
Subject The Unix Programming Environment E210074 entity
Predicate author P4 FINISHED
Object Rob Pike E98914 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: Rob Pike | Statement: [The Unix Programming Environment, author, Rob Pike]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rob Pike
Context triple: [The Unix Programming Environment, author, Rob Pike]
  • A. Rob Pike chosen
    Rob Pike is a Canadian software engineer and author best known as a co-creator of the Go programming language and for his influential work at Bell Labs and Google.
  • B. John Lattner
    John Lattner was a standout halfback for the University of Notre Dame who won the 1953 Heisman Trophy and later played in the NFL.
  • C. L. Peter Deutsch
    L. Peter Deutsch is a computer scientist and software developer best known for creating the Ghostscript interpreter for the PostScript language and PDF files.
  • D. Robert Griesemer
    Robert Griesemer is a Swiss software engineer best known as one of the principal designers of the Go programming language at Google.
  • E. Chris Lattner
    Chris Lattner is a software engineer best known for creating the LLVM compiler infrastructure and leading the development of Apple’s Swift programming language.
  • 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_69ca8365b28081909e48e45e95dfc405 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc604ac0288190b59344bced8ac733 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf896382708190a08c6bacf1157066 completed April 3, 2026, 9:33 a.m.
Created at: March 30, 2026, 6:47 p.m.