Triple

T17175403
Position Surface form Disambiguated ID Type / Status
Subject Siemens SD-160 E416845 entity
Predicate successorModel P16897 FINISHED
Object Siemens S70 E14233 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: Siemens S70 | Statement: [Siemens SD-160, successorModel, Siemens S70]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens S70
Context triple: [Siemens SD-160, successorModel, Siemens S70]
  • A. Siemens S70 chosen
    The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
  • B. Siemens S200
    The Siemens S200 is a modern low-floor light rail vehicle used in North American transit systems, including Calgary’s CTrain, known for its improved accessibility, energy efficiency, and passenger comfort.
  • C. Siemens SD-160
    The Siemens SD-160 is a high-floor light rail vehicle widely used in North American transit systems, including Calgary’s CTrain, known for its modular design and reliable urban service.
  • D. 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.
  • E. Siemens Avanto
    Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc0cec448190b30466628a2ff23f completed April 18, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0148435f6081909bfc6cc1ef59d971 completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.