Triple

T4654788
Position Surface form Disambiguated ID Type / Status
Subject Chris Lattner E102382 entity
Predicate name P16 FINISHED
Object Chris Lattner E102382 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: Chris Lattner | Statement: [Chris Lattner, name, Chris Lattner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chris Lattner
Context triple: [Chris Lattner, name, Chris Lattner]
  • A. Chris Lattner chosen
    Chris Lattner is a software engineer best known for creating the LLVM compiler infrastructure and leading the development of Apple’s Swift programming language.
  • 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. Andy Hertzfeld
    Andy Hertzfeld is a pioneering software engineer best known as a key member of the original Apple Macintosh development team and a co-creator of the Mac’s graphical user interface.
  • 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. Rob Pike
    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.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6317ba70819089145766d3462e57 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaef125c819097d79f25608302dc completed March 21, 2026, 1:57 a.m.
Created at: March 20, 2026, 1:14 p.m.