Triple

T1684781
Position Surface form Disambiguated ID Type / Status
Subject R160 subway cars E36417 entity
Predicate manufacturer P490 FINISHED
Object Alstom E25910 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: Alstom | Statement: [R160 subway cars, manufacturer, Alstom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alstom
Context triple: [R160 subway cars, manufacturer, Alstom]
  • A. Alstom (formerly Bombardier Transportation) chosen
    Alstom (formerly Bombardier Transportation) is a major global rail transport manufacturer known for producing trains, trams, and related railway systems and equipment.
  • B. Siemens Transportation Systems
    Siemens Transportation Systems is a division of Siemens AG that designs and manufactures rail vehicles and related transportation infrastructure and technologies.
  • C. Hitachi Rail
    Hitachi Rail is a global rail transport and engineering company that designs, manufactures, and maintains trains and railway systems for urban, intercity, and high-speed networks.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Stadler Rail
    Stadler Rail is a Swiss manufacturer of railway rolling stock known for producing regional and commuter trains, trams, and light rail vehicles for markets worldwide.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa627c29548190b60ee3bc744069a0 completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71c1b4308190b04fed7ce752b67c completed March 8, 2026, 12:55 p.m.
Created at: March 4, 2026, 7:29 p.m.