Triple

T15558965
Position Surface form Disambiguated ID Type / Status
Subject Hideo Nomo E370945 entity
Predicate familyName P18 FINISHED
Object Nomo
Nomo is a Japanese surname most famously associated with former Major League Baseball pitcher Hideo Nomo, a trailblazer for Japanese players in the United States.
E1163418 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: Nomo | Statement: [Hideo Nomo, familyName, Nomo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nomo
Context triple: [Hideo Nomo, familyName, Nomo]
  • A. Nomo-san
    Nomo-san is the affectionate nickname of Katsuya Nomura, a legendary Japanese baseball catcher and manager renowned for his prolific hitting and strategic acumen.
  • B. Molitor
    Molitor is a surname most notably associated with Paul Molitor, a Hall of Fame Major League Baseball player and manager.
  • C. Tetsuharu
    Tetsuharu is a Japanese given name most famously associated with Tetsuharu Kawakami, a legendary professional baseball player and manager in Japan.
  • D. Boras
    Borås is a city in western Sweden known for its historic textile industry, design heritage, and role as a regional commercial center.
  • E. Mussina
    Mussina is the surname of Mike Mussina, a former Major League Baseball pitcher best known for his successful career with the Baltimore Orioles and New York Yankees.
  • 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: Nomo
Triple: [Hideo Nomo, familyName, Nomo]
Generated description
Nomo is a Japanese surname most famously associated with former Major League Baseball pitcher Hideo Nomo, a trailblazer for Japanese players in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nomo
Target entity description: Nomo is a Japanese surname most famously associated with former Major League Baseball pitcher Hideo Nomo, a trailblazer for Japanese players in the United States.
  • A. Nomo-san
    Nomo-san is the affectionate nickname of Katsuya Nomura, a legendary Japanese baseball catcher and manager renowned for his prolific hitting and strategic acumen.
  • B. Molitor
    Molitor is a surname most notably associated with Paul Molitor, a Hall of Fame Major League Baseball player and manager.
  • C. Tetsuharu
    Tetsuharu is a Japanese given name most famously associated with Tetsuharu Kawakami, a legendary professional baseball player and manager in Japan.
  • D. Boras
    Borås is a city in western Sweden known for its historic textile industry, design heritage, and role as a regional commercial center.
  • E. Mussina
    Mussina is the surname of Mike Mussina, a former Major League Baseball pitcher best known for his successful career with the Baltimore Orioles and New York Yankees.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dda3ab88190ab383333ce69fe8f completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456635588190a2473bcff3ae4a53 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff46f44b2c81909f65f0ab455c6549 completed May 9, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_69ff477a63b48190a453cf669dfda228 completed May 9, 2026, 2:40 p.m.
Created at: April 10, 2026, 4:09 a.m.