Triple

T2370648
Position Surface form Disambiguated ID Type / Status
Subject Jack Murdock E46080 entity
Predicate coFounded P104 FINISHED
Object Tektronix E7900 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: Tektronix | Statement: [Jack Murdock, coFounded, Tektronix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tektronix
Context triple: [Jack Murdock, coFounded, Tektronix]
  • A. Tektronix chosen
    Tektronix is an American company best known for designing and manufacturing electronic test and measurement equipment such as oscilloscopes and signal analyzers.
  • B. National Instruments
    National Instruments is an American company that develops automated test and measurement systems, best known for its LabVIEW graphical programming environment and modular instrumentation hardware.
  • C. Teledyne
    Teledyne is an American industrial conglomerate known for its diversified operations in electronics, instrumentation, aerospace, and digital imaging technologies.
  • D. Agilent Technologies
    Agilent Technologies is a global company specializing in life sciences, diagnostics, and analytical laboratory instruments and services.
  • E. Mentor Graphics
    Mentor Graphics is an American electronic design automation (EDA) company known for its software and hardware tools used to design and verify integrated circuits and electronic systems.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc76f5aec8190867d621e6849258c completed March 7, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8a2b1448190b19179cf379993ee completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:56 p.m.