Triple

T12188285
Position Surface form Disambiguated ID Type / Status
Subject Siemens S200 (Muni LRV4) E290392 entity
Predicate marketedAs P1395 FINISHED
Object LRV4
LRV4 is San Francisco Muni’s modern Siemens S200 light rail vehicle model used on the city’s Muni Metro system.
 E967850 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: LRV4 | Statement: [Siemens S200 (Muni LRV4), marketedAs, LRV4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LRV4
Context triple: [Siemens S200 (Muni LRV4), marketedAs, LRV4]
  • A. LSV
    LSV is the IATA airport code for the military airfield serving Nellis Air Force Base near Las Vegas, Nevada.
  • B. BV-4D
    BV-4D is a high-capacity rechargeable lithium-ion battery designed for use in select Nokia smartphones, notably camera-focused models.
  • C. BRV
    BRV is the National Rail station code for Bournville railway station in Birmingham, England.
  • D. NV-4
    NV-4 is the designation for Nevada's 4th congressional district, a U.S. House of Representatives district covering parts of central and southern Nevada.
  • E. Type 8 LRV
    The Type 8 LRV is a low-floor light rail vehicle used by Boston’s MBTA on its Green Line, designed to improve accessibility and passenger comfort.
  • 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: LRV4
Triple: [Siemens S200 (Muni LRV4), marketedAs, LRV4]
Generated description
LRV4 is San Francisco Muni’s modern Siemens S200 light rail vehicle model used on the city’s Muni Metro system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LRV4
Target entity description: LRV4 is San Francisco Muni’s modern Siemens S200 light rail vehicle model used on the city’s Muni Metro system.
  • A. LSV
    LSV is the IATA airport code for the military airfield serving Nellis Air Force Base near Las Vegas, Nevada.
  • B. BV-4D
    BV-4D is a high-capacity rechargeable lithium-ion battery designed for use in select Nokia smartphones, notably camera-focused models.
  • C. BRV
    BRV is the National Rail station code for Bournville railway station in Birmingham, England.
  • D. NV-4
    NV-4 is the designation for Nevada's 4th congressional district, a U.S. House of Representatives district covering parts of central and southern Nevada.
  • E. Type 8 LRV
    The Type 8 LRV is a low-floor light rail vehicle used by Boston’s MBTA on its Green Line, designed to improve accessibility and passenger comfort.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c5102848190ad652c3d6445f65a completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6b0a84c8190ae593e368c13b5a5 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f600b7e1788190b1df4fdfd96118d0 completed May 2, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_69f604c4ef7c8190bc128b1aa535744d completed May 2, 2026, 2:05 p.m.
Created at: April 8, 2026, 9:50 p.m.