Triple

T21705006
Position Surface form Disambiguated ID Type / Status
Subject Pons HP 40 E535749 entity
Predicate usesChassis P66199 FINISHED
Object Kalex NE NERFINISHED

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: Kalex | Statement: [Pons HP 40, usesChassis, Kalex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kalex
Context triple: [Pons HP 40, usesChassis, Kalex]
  • A. Kalex chosen
    Kalex is a German racing motorcycle chassis manufacturer best known for its dominant, championship-winning frames in the Moto2 World Championship.
  • B. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • C. Kawasaki More’s
    Kawasaki More’s is a shopping complex located in Kawasaki-ku, Japan, offering a variety of retail stores, dining options, and services.
  • D. Kawasaki Daishi
    Kawasaki Daishi is a major Shingon Buddhist temple in Kawasaki, Japan, renowned as a popular site for New Year’s visits and prayers for protection from misfortune.
  • E. Puch
    Puch is a locality that forms part of the municipality of Puch bei Hallein in the Austrian state of Salzburg.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efb52e4b84819095a24cc9fdca2b8a completed April 27, 2026, 7:12 p.m.
Created at: April 16, 2026, 6:46 p.m.