Triple

T3831921
Position Surface form Disambiguated ID Type / Status
Subject MG ZS E91031 entity
Predicate competitor P1375 FINISHED
Object Nissan Juke E126342 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: Nissan Juke | Statement: [MG ZS, competitor, Nissan Juke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nissan Juke
Context triple: [MG ZS, competitor, Nissan Juke]
  • A. Nissan Juke chosen
    The Nissan Juke is a subcompact crossover SUV known for its distinctive, unconventional styling and sporty driving character.
  • B. Nissan Qashqai
    The Nissan Qashqai is a compact crossover SUV popular for its practical size, fuel efficiency, and family-friendly versatility, especially in European markets.
  • C. Nissan Micra
    The Nissan Micra is a long-running subcompact hatchback car known for its small size, fuel efficiency, and popularity in urban markets worldwide.
  • D. Nissan Rogue
    The Nissan Rogue is a compact crossover SUV known for its practicality, fuel efficiency, and family-friendly features.
  • E. Jeep Compass
    The Jeep Compass is a compact crossover SUV known for combining everyday practicality with Jeep’s signature off-road capability and rugged styling.
  • 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_69aed960b538819096561c8ed448dec9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb8787bc8190819a7af975b609df completed March 9, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503fcddb481909690b708754d3d8a completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:17 p.m.