Triple

T122027
Position Surface form Disambiguated ID Type / Status
Subject MAX Red Line E2466 entity
Predicate rollingStock P1305 FINISHED
Object Siemens S70
The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
E14233 NE FINISHED

How this triple was built (4 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 S70 | Statement: [MAX Red Line, rollingStock, Siemens S70]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siemens S70
Context triple: [MAX Red Line, rollingStock, Siemens S70]
  • A. Siemens SD660
    Siemens SD660 is a model of light rail vehicle built by Siemens for use in modern urban transit systems.
  • B. Rockwell
    Rockwell is an American singer and songwriter best known for his 1984 hit single "Somebody's Watching Me."
  • C. Saab Automobile
    Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
  • D. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • E. Weisser Clevner
    Weisser Clevner is a white wine grape variety better known internationally as Chardonnay, one of the world’s most widely planted and versatile wine grapes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Siemens S70
Triple: [MAX Red Line, rollingStock, Siemens S70]
Generated description
The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Siemens S70
Target entity description: The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
  • A. Siemens SD660
    Siemens SD660 is a model of light rail vehicle built by Siemens for use in modern urban transit systems.
  • B. Rockwell
    Rockwell is an American singer and songwriter best known for his 1984 hit single "Somebody's Watching Me."
  • C. Saab Automobile
    Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
  • D. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • E. Weisser Clevner
    Weisser Clevner is a white wine grape variety better known internationally as Chardonnay, one of the world’s most widely planted and versatile wine grapes.
  • F. None of above. chosen

Provenance (5 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a25739ef28819093f3f0e6bb670201 completed Feb. 28, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e494ef08190b8c5b5f8d52251c8 completed Feb. 28, 2026, 7:50 a.m.
NEDg Description generation batch_69a29eb86f5c819081da2fd6275d6f78 completed Feb. 28, 2026, 7:52 a.m.
NED2 Entity disambiguation (via description) batch_69a2a04c4cc88190b8741fa48a158dc2 completed Feb. 28, 2026, 7:59 a.m.
Created at: Feb. 28, 2026, 2:24 a.m.