Triple

T7328824
Position Surface form Disambiguated ID Type / Status
Subject Mentor Graphics E168945 entity
Predicate formerName P65 FINISHED
Object Mentor, a Siemens Business E49800 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: Mentor, a Siemens Business | Statement: [Mentor Graphics, formerName, Mentor, a Siemens Business]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mentor, a Siemens Business
Context triple: [Mentor Graphics, formerName, Mentor, a Siemens Business]
  • A. Siemens Venture coaches
    Siemens Venture coaches are modern, lightweight passenger railcars built by Siemens Mobility for higher-speed, intercity and regional train services in North America.
  • B. Siemens Avanto
    Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport systems.
  • C. Siemens Nexas
    Siemens Nexas is a class of electric multiple unit trains used for suburban passenger services on Melbourne’s metropolitan rail network.
  • D. Siemens chosen
    Siemens is a major German multinational conglomerate best known for its leading roles in industrial manufacturing, energy, healthcare technology, and infrastructure solutions worldwide.
  • E. Siemens SD100
    The Siemens SD100 is a light rail vehicle model built by Siemens for use on urban trolley and light rail systems such as the San Diego Trolley.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0a879b88190bef0fb6cbae411ff completed March 27, 2026, 9:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ef16f35881909fffba1df072f0d6 completed March 28, 2026, 3:09 p.m.
Created at: March 27, 2026, 3:03 p.m.