Triple

T16179181
Position Surface form Disambiguated ID Type / Status
Subject MG Cars E392642 entity
Predicate parentOrganization P254 FINISHED
Object MG Rover Group E394883 NE 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: MG Rover Group | Statement: [MG Cars, parentOrganization, MG Rover Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MG Rover Group
Context triple: [MG Cars, parentOrganization, MG Rover Group]
  • A. MG Rover Group chosen
    MG Rover Group was a British car manufacturer formed from the remnants of the Rover Group, known for producing MG and Rover-branded vehicles before its collapse in 2005.
  • B. Rover Group
    Rover Group was a major British automotive manufacturer best known for producing Rover, Mini, and Land Rover vehicles before its breakup in the late 20th and early 21st centuries.
  • C. Jaguar Land Rover
    Jaguar Land Rover is a British multinational automotive company known for designing and manufacturing luxury vehicles under the Jaguar and Land Rover brands.
  • D. Land Rover
    Land Rover is a British automotive brand renowned for its rugged, luxury four-wheel-drive vehicles and long association with off-road exploration and adventure.
  • E. Alvis Vehicles
    Alvis Vehicles was a British manufacturer known for producing military armored vehicles and reconnaissance platforms for the British Army and international customers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205b88b481908ecdd8d663dc668b completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000787d3fc8190a32d53a177fedb6d completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:02 a.m.