Triple

T14222858
Position Surface form Disambiguated ID Type / Status
Subject Ei-ichi Negishi E352540 entity
Predicate familyName P18 FINISHED
Object Negishi
Negishi is a Japanese surname most notably associated with Nobel Prize–winning chemist Ei-ichi Negishi, known for the Negishi coupling reaction in organic synthesis.
 E1088595 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: Negishi | Statement: [Ei-ichi Negishi, familyName, Negishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Negishi
Context triple: [Ei-ichi Negishi, familyName, Negishi]
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Morishita
    Morishita is a neighborhood in Tokyo, Japan, known for its traditional shitamachi atmosphere, residential streets, and convenient access to central city areas.
  • C. Yamauchi
    Yamauchi is a Japanese surname notably associated with the founding family of Nintendo and other prominent historical figures in Japan.
  • D. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • E. Yamazoe
    Yamazoe is a rural village in Nara Prefecture, Japan, known for its mountainous terrain, forests, and traditional countryside landscapes.
  • 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: Negishi
Triple: [Ei-ichi Negishi, familyName, Negishi]
Generated description
Negishi is a Japanese surname most notably associated with Nobel Prize–winning chemist Ei-ichi Negishi, known for the Negishi coupling reaction in organic synthesis.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Negishi
Target entity description: Negishi is a Japanese surname most notably associated with Nobel Prize–winning chemist Ei-ichi Negishi, known for the Negishi coupling reaction in organic synthesis.
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Morishita
    Morishita is a neighborhood in Tokyo, Japan, known for its traditional shitamachi atmosphere, residential streets, and convenient access to central city areas.
  • C. Yamauchi
    Yamauchi is a Japanese surname notably associated with the founding family of Nintendo and other prominent historical figures in Japan.
  • D. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • E. Yamazoe
    Yamazoe is a rural village in Nara Prefecture, Japan, known for its mountainous terrain, forests, and traditional countryside landscapes.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6227c288819081473ce44f9f0934 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd2813e55881909bdbc6f3c6ef572b completed May 8, 2026, 12:02 a.m.
NEDg Description generation batch_69fd2b0956948190bf654403ad0b154a completed May 8, 2026, 12:15 a.m.
NED2 Entity disambiguation (via description) batch_69fd2df66aa48190ae18a4ca1c099c25 completed May 8, 2026, 12:27 a.m.
Created at: April 10, 2026, 1:06 a.m.