Triple

T2567299
Position Surface form Disambiguated ID Type / Status
Subject Minoru Yamasaki E57382 entity
Predicate givenName P17 FINISHED
Object Minoru
Minoru is a Japanese given name commonly used for males and borne by several notable figures in fields such as architecture, sports, and entertainment.
 E287317 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: Minoru | Statement: [Minoru Yamasaki, givenName, Minoru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Minoru
Context triple: [Minoru Yamasaki, givenName, Minoru]
  • A. Itami
    Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
  • B. Miyazu
    Miyazu is a coastal city in northern Kyoto Prefecture, Japan, best known as the gateway to the scenic sandbar Amanohashidate, one of Japan’s traditional “Three Views.”
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Masayuki
    Masayuki is a Japanese given name commonly used for males.
  • E. Mamoru
    Mamoru is a Japanese masculine given name commonly borne by notable figures in politics, arts, and entertainment.
  • 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: Minoru
Triple: [Minoru Yamasaki, givenName, Minoru]
Generated description
Minoru is a Japanese given name commonly used for males and borne by several notable figures in fields such as architecture, sports, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Minoru
Target entity description: Minoru is a Japanese given name commonly used for males and borne by several notable figures in fields such as architecture, sports, and entertainment.
  • A. Itami
    Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
  • B. Miyazu
    Miyazu is a coastal city in northern Kyoto Prefecture, Japan, best known as the gateway to the scenic sandbar Amanohashidate, one of Japan’s traditional “Three Views.”
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Masayuki
    Masayuki is a Japanese given name commonly used for males.
  • E. Mamoru
    Mamoru is a Japanese masculine given name commonly borne by notable figures in politics, arts, and entertainment.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3602ed08190aad0f9c7ac577eb0 completed March 7, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa046b09c8190a03f6a24ae1a1d6e completed March 10, 2026, 4:38 a.m.
NEDg Description generation batch_69afa1196aac81909b25557dff5acf5e completed March 10, 2026, 4:42 a.m.
NED2 Entity disambiguation (via description) batch_69afa1a7d9b48190a8b14a7d209e1f26 completed March 10, 2026, 4:44 a.m.
Created at: March 6, 2026, 9:48 p.m.