Triple

T712175
Position Surface form Disambiguated ID Type / Status
Subject Siemens S70 E14233 entity
Predicate successor P78 FINISHED
Object Siemens S700 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 S700 | Statement: [Siemens S70, successor, Siemens S700]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens S700
Context triple: [Siemens S70, successor, Siemens S700]
  • 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 SD660
    Siemens SD660 is a model of light rail vehicle built by Siemens for use in modern urban transit systems.
  • C. Siemens
    Siemens is a major German multinational conglomerate best known for its leading roles in industrial manufacturing, energy, healthcare technology, and infrastructure solutions worldwide.
  • D. Siemens Charger
    The Siemens Charger is a family of modern diesel-electric passenger locomotives widely used across North America for intercity and commuter rail services.
  • E. Siemens ACS-64
    The Siemens ACS-64 is a high-speed, electric locomotive used by Amtrak for passenger rail service in the United States.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55dd5908190bfb8816f65ea02e1 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a63757e5848190b7c11820f67b20a7 completed March 3, 2026, 1:20 a.m.
Created at: March 1, 2026, 7:36 p.m.