Triple

T16179878
Position Surface form Disambiguated ID Type / Status
Subject Morris Garages E392656 entity
Predicate notableModel P1503 FINISHED
Object MG Hector E392644 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 Hector | Statement: [Morris Garages, notableModel, MG Hector]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MG Hector
Context triple: [Morris Garages, notableModel, MG Hector]
  • A. MG Hector chosen
    The MG Hector is a mid-size SUV produced by MG Motor, known for its connected-car technology, spacious interior, and strong value proposition in markets like India.
  • B. Marshal Victor
    Marshal Victor was a prominent French military leader and marshal of the First French Empire who distinguished himself in numerous Napoleonic campaigns.
  • C. Coronel
    Coronel is a coastal city in south-central Chile known for its historic coal-mining industry and fishing activities along the Pacific Ocean.
  • D. Gourette
    Gourette is a French mountain ski resort village in the Pyrenees, known for its alpine slopes and scenic high-altitude setting.
  • E. Catroux
    Catroux is a French surname most notably borne by Georges Catroux, a prominent French general and diplomat of the 20th century.
  • 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_69d87f1e49ac8190a311b54d32990576 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_69ffff0022148190bc1810e76cf6d994 completed May 10, 2026, 3:44 a.m.
Created at: April 10, 2026, 5:02 a.m.