Triple

T4654838
Position Surface form Disambiguated ID Type / Status
Subject Chris Lattner E102382 entity
Predicate coFounded P104 FINISHED
Object Modular Inc. E457338 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: Modular Inc. | Statement: [Chris Lattner, coFounded, Modular Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Modular Inc.
Context triple: [Chris Lattner, coFounded, Modular Inc.]
  • A. Modular Inc. chosen
    Modular Inc. is a technology company co-founded by LLVM and Swift creator Chris Lattner that focuses on building next-generation AI infrastructure and developer tools.
  • B. Nexter Systems
    Nexter Systems is a French defense company specializing in the design and manufacture of military land systems, including armored vehicles, artillery, and ammunition.
  • C. Cybus Industries
    Cybus Industries is a powerful fictional technology conglomerate in the Doctor Who universe, best known for creating an alternate-universe version of the Cybermen.
  • D. Invetech
    Invetech is a technology and product development company specializing in designing and engineering innovative medical and life science solutions.
  • E. Kronos Incorporated
    Kronos Incorporated was a workforce management and human capital management software company best known for its timekeeping, scheduling, and HR solutions used by organizations worldwide.
  • 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_69be0378825881908fe3214f60be579e completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:14 p.m.