Triple

T11111278
Position Surface form Disambiguated ID Type / Status
Subject M1 E262760 entity
Predicate hasRollingStockType P1305 FINISHED
Object Siemens Inspiro E262774 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 Inspiro | Statement: [M1, hasRollingStockType, Siemens Inspiro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens Inspiro
Context triple: [M1, hasRollingStockType, Siemens Inspiro]
  • A. Siemens Inspiro chosen
    Siemens Inspiro is a modern, modular metro train platform developed by Siemens for urban rapid transit systems worldwide.
  • 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 U2
    Siemens U2 is a type of light rail vehicle widely used in North American transit systems, including the San Diego Trolley, known for its articulated design and high-floor configuration.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a6964508190b679303d3b3a4fd6 completed April 9, 2026, 12:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d759bc88190b670c373f3647a41 completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:27 p.m.