Triple

T11657475
Position Surface form Disambiguated ID Type / Status
Subject Sharp E277046 entity
Predicate originalName P65 FINISHED
Object Hayakawa Metal Works E383930 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: Hayakawa Metal Works | Statement: [Sharp, originalName, Hayakawa Metal Works]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hayakawa Metal Works
Context triple: [Sharp, originalName, Hayakawa Metal Works]
  • A. Hayakawa Metal Works chosen
    Hayakawa Metal Works was the original manufacturing company founded by Tokuji Hayakawa in Japan that later evolved into the global electronics firm Sharp Corporation.
  • B. Kawada Industries
    Kawada Industries is a Japanese engineering and construction company known for its work on major infrastructure projects, including prominent bridges and civil works.
  • C. Yoshimoto Kogyo
    Yoshimoto Kogyo is a major Japanese entertainment conglomerate best known for managing comedians and producing comedy shows, theater, television, and other media.
  • D. Komatsu Limited
    Komatsu Limited is a major Japanese multinational corporation that manufactures construction, mining, and military equipment.
  • E. Obayashi Corporation
    Obayashi Corporation is a major Japanese construction and engineering company known for its involvement in large-scale infrastructure and building projects worldwide.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a3d0331481909682b2e504e4c9a0 completed April 10, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee88166900819095063f045be44bed completed April 26, 2026, 9:48 p.m.
Created at: April 8, 2026, 9:39 p.m.