Triple

T3765924
Position Surface form Disambiguated ID Type / Status
Subject TGV POS E82676 entity
Predicate manufacturer P490 FINISHED
Object Alstom E264558 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: [TGV POS, manufacturer, Alstom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alstom
Context triple: [TGV POS, manufacturer, Alstom]
  • A. Alstom (formerly Bombardier Transportation)
    Alstom (formerly Bombardier Transportation) is a major global rail transport manufacturer known for producing trains, trams, and related railway systems and equipment.
  • B. Alcatel Alsthom chosen
    Alcatel Alsthom was a major French industrial conglomerate active in telecommunications, power generation, and transport infrastructure before being restructured and rebranded as Alcatel.
  • C. Siemens Transportation Systems
    Siemens Transportation Systems is a division of Siemens AG that designs and manufactures rail vehicles and related transportation infrastructure and technologies.
  • D. 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.
  • E. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbfeb52081909c38103beb5dbdcd completed March 8, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5221ab08190a3599afbbd5dbc6e completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.