Triple

T3777408
Position Surface form Disambiguated ID Type / Status
Subject Z 5600 E83340 entity
Predicate builder P3143 FINISHED
Object Alsthom 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: Alsthom | Statement: [Z 5600, builder, Alsthom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsthom
Context triple: [Z 5600, builder, Alsthom]
  • A. 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.
  • B. 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.
  • C. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • D. Siemens Transportation Systems
    Siemens Transportation Systems is a division of Siemens AG that designs and manufactures rail vehicles and related transportation infrastructure and technologies.
  • E. 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.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5d3dbc8190b6ab118a56acd5a3 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f03d3df48190a4b2382059b7bb24 completed March 14, 2026, 5:21 a.m.
Created at: March 8, 2026, 3:36 p.m.