Triple

T17023032
Position Surface form Disambiguated ID Type / Status
Subject AVIDAC E412991 entity
Predicate influencedBy P9 FINISHED
Object IAS machine E87767 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: IAS machine | Statement: [AVIDAC, influencedBy, IAS machine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IAS machine
Context triple: [AVIDAC, influencedBy, IAS machine]
  • A. IAS machine chosen
    The IAS machine was an early electronic stored-program computer designed by John von Neumann and his colleagues at the Institute for Advanced Study, serving as a prototype for many subsequent computer architectures.
  • B. Isa Machine
    Isa Machine is the stage name of Isabella Summers, the English musician, producer, and keyboardist best known as a founding member of Florence + The Machine.
  • C. NuMachine
    NuMachine was an early 1980s experimental workstation computer project at MIT that pioneered the NuBus expansion bus architecture.
  • D. the Machine
    The Machine is a notorious torture device from "The Princess Bride" that painfully drains years of life from its victims.
  • E. Intelligence Processing Unit
    The Intelligence Processing Unit is a specialized processor architecture designed by Graphcore to accelerate artificial intelligence and machine learning workloads with highly parallel, memory-rich compute.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d2abbc81908943becf5f539fc6 completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012334c3b48190b125ab926450c45b completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:33 a.m.