Triple

T29448111
Position Surface form Disambiguated ID Type / Status
Subject CSeries E746904 entity
Predicate typicalSeatingCS100 P196486 FINISHED
Object 100–125 passengers LITERAL 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: 100–125 passengers | Statement: [CSeries, typicalSeatingCS100, 100–125 passengers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalSeatingCS100
Context triple: [CSeries, typicalSeatingCS100, 100–125 passengers]
  • A. typicalSeat
    Indicates the usual or standard seating position or location associated with an entity in a given context.
  • B. seatingConfiguration
    Indicates how seats are arranged or organized relative to each other in a given context.
  • C. typicalSeatCount chosen
    Indicates the usual or standard number of seats associated with an entity.
  • D. classesOfSeats
    Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
  • E. hasFlexibleSeating
    Indicates that an entity provides seating arrangements that can be easily rearranged, adjusted, or reconfigured to suit different uses or preferences.
  • F. None of above.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_6a01c21d8bc481909dd9f5a6b89c0a92 completed May 11, 2026, 11:48 a.m.
PD Predicate disambiguation batch_6a01bff5d1508190895e5bd2c04932b0 completed May 11, 2026, 11:39 a.m.
Created at: April 28, 2026, 3:29 p.m.