Triple

T17253347
Position Surface form Disambiguated ID Type / Status
Subject Hyundai i10 E418812 entity
Predicate competitor P1375 FINISHED
Object Suzuki Celerio E1234188 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: Suzuki Celerio | Statement: [Hyundai i10, competitor, Suzuki Celerio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzuki Celerio
Context triple: [Hyundai i10, competitor, Suzuki Celerio]
  • A. Suzuki Swift
    The Suzuki Swift is a popular subcompact hatchback car known for its nimble handling, fuel efficiency, and value-oriented pricing in global markets.
  • B. Celerio chosen
    Celerio is a compact hatchback car produced by Maruti Suzuki, known for its fuel efficiency and suitability for urban driving.
  • C. Suzuki Baleno
    The Suzuki Baleno is a compact car produced by Suzuki, known for its practicality, fuel efficiency, and popularity in emerging markets.
  • D. Suzuki Alto
    The Suzuki Alto is a long-running line of compact city cars known for their affordability, fuel efficiency, and popularity in markets worldwide.
  • E. Suzuki Wagon R
    The Suzuki Wagon R is a popular Japanese kei car and compact hatchback known for its tall, boxy design that maximizes interior space and practicality in a small footprint.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e6a1b648190a8bb2deb67bbdfdc completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170fb89248190ae431ce51dfeaffd completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.