Triple

T6931183
Position Surface form Disambiguated ID Type / Status
Subject KDDI E160435 entity
Predicate legalForm P64 FINISHED
Object Kabushiki gaisha E381838 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: Kabushiki gaisha | Statement: [KDDI, legalForm, Kabushiki gaisha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabushiki gaisha
Context triple: [KDDI, legalForm, Kabushiki gaisha]
  • A. Kabushiki gaisha chosen
    Kabushiki gaisha is a common Japanese joint-stock company structure similar to a corporation, used by many major businesses in Japan.
  • B. Keio Corporation
    Keio Corporation is a major Japanese private railway and transportation company operating rail lines and related services in the Tokyo metropolitan area.
  • C. Nippon Kobo
    Nippon Kobo was a Japanese design and architecture firm active in the mid-20th century, known for its collaborations with prominent modernist designers such as Charlotte Perriand.
  • D. Taisei Corporation
    Taisei Corporation is a major Japanese construction and civil engineering company known for leading large-scale infrastructure and landmark building projects in Japan and abroad.
  • E. Keihan Group
    Keihan Group is a Japanese corporate conglomerate centered on the Keihan Electric Railway that operates transportation, real estate, retail, and leisure businesses in the Kansai region.
  • 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_69c6884e15208190b9e91487eaafcf85 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da3e58f08190857c14f538448039 completed March 27, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7514b0dd8819097a3fa1a38c913f4 completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:27 p.m.