Triple

T14933167
Position Surface form Disambiguated ID Type / Status
Subject Yūsaku Kamekura E372320 entity
Predicate familyName P18 FINISHED
Object Kamekura
Kamekura is a Japanese surname most notably associated with Yūsaku Kamekura, a pioneering graphic designer known for his influential modernist posters and logos.
 E1294900 NE FINISHED

How this triple was built (4 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: Kamekura | Statement: [Yūsaku Kamekura, familyName, Kamekura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kamekura
Context triple: [Yūsaku Kamekura, familyName, Kamekura]
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • C. Hiranaka
    Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
  • D. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • E. Yukuhashi
    Yukuhashi is a city in eastern Fukuoka Prefecture, Japan, known as a regional commercial and transportation hub on Kyushu.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kamekura
Triple: [Yūsaku Kamekura, familyName, Kamekura]
Generated description
Kamekura is a Japanese surname most notably associated with Yūsaku Kamekura, a pioneering graphic designer known for his influential modernist posters and logos.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kamekura
Target entity description: Kamekura is a Japanese surname most notably associated with Yūsaku Kamekura, a pioneering graphic designer known for his influential modernist posters and logos.
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • C. Hiranaka
    Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
  • D. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • E. Yukuhashi
    Yukuhashi is a city in eastern Fukuoka Prefecture, Japan, known as a regional commercial and transportation hub on Kyushu.
  • F. None of above. chosen

Provenance (5 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded646a0808190ba5c0c91bde011c5 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a031b0f51608190823a58d75c2a0ac4 completed May 12, 2026, 12:20 p.m.
NEDg Description generation batch_6a031c0821dc8190bfa7860409f0e4a9 completed May 12, 2026, 12:24 p.m.
NED2 Entity disambiguation (via description) batch_6a031cc67f7881908933c14a5386fb25 completed May 12, 2026, 12:27 p.m.
Created at: April 10, 2026, 2:37 a.m.