Triple

T24650132
Position Surface form Disambiguated ID Type / Status
Subject Messerschmitt KR200 E610225 entity
Predicate fuelEconomy P62021 FINISHED
Object approximately 3 L/100 km 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: approximately 3 L/100 km | Statement: [Messerschmitt KR200, fuelEconomy, approximately 3 L/100 km]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fuelEconomy
Context triple: [Messerschmitt KR200, fuelEconomy, approximately 3 L/100 km]
  • A. fuelEfficiency
    Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
  • B. fuelConsumption chosen
    Indicates the amount of fuel used by an entity (such as a vehicle or device) over a specified distance, time, or operation.
  • C. associatedWithFuelEconomy
    Indicates a relationship where something is connected or relevant to fuel economy, such as influencing, measuring, or describing fuel efficiency.
  • D. fuelTransport
    Indicates the transfer or conveyance of fuel from one location or entity to another.
  • E. typicalFuel
    Indicates the kind of fuel that is normally or most commonly used by an entity (such as a device, vehicle, or system).
  • 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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f41011d8048190be70329ba0bfb7c7 completed May 1, 2026, 2:29 a.m.
PD Predicate disambiguation batch_69f40ed9d47881909fcfc0d04e8d074a completed May 1, 2026, 2:24 a.m.
Created at: April 18, 2026, 2:33 a.m.