Triple

T16777884
Position Surface form Disambiguated ID Type / Status
Subject Suzuki Baleno E407774 entity
Predicate competitor P1375 FINISHED
Object Hyundai i20 E1201351 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: Hyundai i20 | Statement: [Suzuki Baleno, competitor, Hyundai i20]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyundai i20
Context triple: [Suzuki Baleno, competitor, Hyundai i20]
  • A. Hyundai i20 chosen
    The Hyundai i20 is a subcompact hatchback produced by Hyundai, known for its practicality, modern features, and strong value in global small-car markets.
  • B. Hyundai i10
    The Hyundai i10 is a compact city car produced by the South Korean manufacturer Hyundai, known for its practicality, affordability, and efficiency in urban driving.
  • C. Hyundai HB20
    The Hyundai HB20 is a popular subcompact hatchback (and sedan) developed for the Brazilian market, known for its modern design, efficient engines, and strong value proposition in the entry-level segment.
  • D. Celerio
    Celerio is a compact hatchback car produced by Maruti Suzuki, known for its fuel efficiency and suitability for urban driving.
  • E. Hyundai Creta
    The Hyundai Creta is a popular compact SUV known for its modern design, feature-rich cabin, and strong sales in markets like India and other emerging economies.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b212fc248190a8fe1124853bf16d completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0911488190a65c1dc536b6ea3e completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:22 a.m.