Triple

T3411664
Position Surface form Disambiguated ID Type / Status
Subject 朝永振一郎 E71909 entity
Predicate 共同受賞者 P1859 FINISHED
Object ジュリアン・シュウィンガー
ジュリアン・シュウィンガーは、量子電磁力学の発展に決定的な貢献をし、場の量子論の形式化で知られるアメリカの理論物理学者です。
 E355492 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: ジュリアン・シュウィンガー | Statement: [朝永振一郎, 共同受賞者, ジュリアン・シュウィンガー]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ジュリアン・シュウィンガー
Context triple: [朝永振一郎, 共同受賞者, ジュリアン・シュウィンガー]
  • A. Christian Weiss
    Christian Weiss is a relatively obscure individual whose specific public notability is not clearly established from the given information.
  • B. Sebastian Maltz
    Sebastian Maltz is an actor known for his role in the television drama series "Patrick Melrose."
  • C. Christopher Scholz
    Christopher Scholz is a prominent geophysicist renowned for his influential work on the mechanics of earthquakes and faulting.
  • D. Nico Habermann
    Nico Habermann was a German-American computer scientist known for his contributions to programming languages, operating systems, and software engineering, and for his influential academic leadership at Carnegie Mellon University.
  • E. Julian Wass
    Julian Wass is a film and television composer known for creating emotionally resonant scores, including the music for the coming-of-age drama "The Miseducation of Cameron Post."
  • 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: ジュリアン・シュウィンガー
Triple: [朝永振一郎, 共同受賞者, ジュリアン・シュウィンガー]
Generated description
ジュリアン・シュウィンガーは、量子電磁力学の発展に決定的な貢献をし、場の量子論の形式化で知られるアメリカの理論物理学者です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ジュリアン・シュウィンガー
Target entity description: ジュリアン・シュウィンガーは、量子電磁力学の発展に決定的な貢献をし、場の量子論の形式化で知られるアメリカの理論物理学者です。
  • A. Christian Weiss
    Christian Weiss is a relatively obscure individual whose specific public notability is not clearly established from the given information.
  • B. Sebastian Maltz
    Sebastian Maltz is an actor known for his role in the television drama series "Patrick Melrose."
  • C. Christopher Scholz
    Christopher Scholz is a prominent geophysicist renowned for his influential work on the mechanics of earthquakes and faulting.
  • D. Nico Habermann
    Nico Habermann was a German-American computer scientist known for his contributions to programming languages, operating systems, and software engineering, and for his influential academic leadership at Carnegie Mellon University.
  • E. Julian Wass
    Julian Wass is a film and television composer known for creating emotionally resonant scores, including the music for the coming-of-age drama "The Miseducation of Cameron Post."
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb90a76288190b92ef3b26638cd47 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdf81e48190abac8ea645e929ce completed March 12, 2026, 11:27 p.m.
NEDg Description generation batch_69b34e4972008190af3b84f26b4a3629 completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b34fc6c3f88190ba1a08243232df05 completed March 12, 2026, 11:44 p.m.
Created at: March 8, 2026, 3:15 p.m.