Triple

T6811623
Position Surface form Disambiguated ID Type / Status
Subject Intercity direct E156646 entity
Predicate usesRollingStock P5426 FINISHED
Object NS VIRM
NS VIRM is a series of Dutch double-decker electric multiple-unit trains operated by Nederlandse Spoorwegen for high-capacity intercity services.
 E620583 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: NS VIRM | Statement: [Intercity direct, usesRollingStock, NS VIRM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NS VIRM
Context triple: [Intercity direct, usesRollingStock, NS VIRM]
  • A. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • B. VNF
    VNF is the French public agency responsible for managing and developing the country’s inland waterways network.
  • C. VMU
    The VMU (Visual Memory Unit) is a memory card and secondary screen accessory for the Sega Dreamcast that provides game save storage and mini-game functionality.
  • D. VNS
    VNS is the IATA airport code for Lal Bahadur Shastri International Airport serving Varanasi, India.
  • E. VMC
    VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
  • 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: NS VIRM
Triple: [Intercity direct, usesRollingStock, NS VIRM]
Generated description
NS VIRM is a series of Dutch double-decker electric multiple-unit trains operated by Nederlandse Spoorwegen for high-capacity intercity services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NS VIRM
Target entity description: NS VIRM is a series of Dutch double-decker electric multiple-unit trains operated by Nederlandse Spoorwegen for high-capacity intercity services.
  • A. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • B. VNF
    VNF is the French public agency responsible for managing and developing the country’s inland waterways network.
  • C. VMU
    The VMU (Visual Memory Unit) is a memory card and secondary screen accessory for the Sega Dreamcast that provides game save storage and mini-game functionality.
  • D. VNS
    VNS is the IATA airport code for Lal Bahadur Shastri International Airport serving Varanasi, India.
  • E. VMC
    VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
  • 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d327e37081909d576e6eff9eec97 completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71aa7dc3c81909ef422b5c51ae6be completed March 28, 2026, 12:02 a.m.
NEDg Description generation batch_69c71e7cd6448190845888760c677eda completed March 28, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_69c71edd37048190bf4de088ad9f11de completed March 28, 2026, 12:20 a.m.
Created at: March 27, 2026, 2:16 p.m.