Triple

T2716417
Position Surface form Disambiguated ID Type / Status
Subject LLVM E59978 entity
Predicate originalDeveloper P184 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: [LLVM, originalDeveloper, Chris Lattner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chris Lattner
Context triple: [LLVM, originalDeveloper, 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda964d4881908179b2a1b16411e4 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb68a3cb881909fd29018154ae4d3 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.