Triple

T13070136
Position Surface form Disambiguated ID Type / Status
Subject Anpanman picture books E329433 entity
Predicate featureCharacter P23263 FINISHED
Object Jam Ojisan
Jam Ojisan is a kindly baker character in the Anpanman series who creates the hero Anpanman and other bread-based characters.
 E1020418 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: Jam Ojisan | Statement: [Anpanman picture books, featureCharacter, Jam Ojisan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jam Ojisan
Context triple: [Anpanman picture books, featureCharacter, Jam Ojisan]
  • A. Jiro
    Jiro is a masculine Japanese given name commonly associated with notable figures in Japanese culture, including engineers, artists, and fictional characters.
  • B. Tajōmaru
    Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
  • C. Ikujiro
    Ikujiro is a Japanese organizational theorist best known for his work on knowledge management and the SECI model of knowledge creation.
  • D. Tarō
    Tarō is a common Japanese masculine given name, often written with kanji meaning "eldest son" and frequently used in traditional and modern Japanese culture.
  • E. Seiji
    Seiji is a Japanese given name most famously associated with the renowned conductor Seiji Ozawa.
  • 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: Jam Ojisan
Triple: [Anpanman picture books, featureCharacter, Jam Ojisan]
Generated description
Jam Ojisan is a kindly baker character in the Anpanman series who creates the hero Anpanman and other bread-based characters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jam Ojisan
Target entity description: Jam Ojisan is a kindly baker character in the Anpanman series who creates the hero Anpanman and other bread-based characters.
  • A. Jiro
    Jiro is a masculine Japanese given name commonly associated with notable figures in Japanese culture, including engineers, artists, and fictional characters.
  • B. Tajōmaru
    Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
  • C. Ikujiro
    Ikujiro is a Japanese organizational theorist best known for his work on knowledge management and the SECI model of knowledge creation.
  • D. Tarō
    Tarō is a common Japanese masculine given name, often written with kanji meaning "eldest son" and frequently used in traditional and modern Japanese culture.
  • E. Seiji
    Seiji is a Japanese given name most famously associated with the renowned conductor Seiji Ozawa.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ee6130819095d835e7ff6a8c5b completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d60510dc81909e0cba8b63a50d9c completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6dbb4b8848190825102be81ff693a completed May 3, 2026, 5:23 a.m.
NED2 Entity disambiguation (via description) batch_69f6dc705f28819087e5d374f83d3acc completed May 3, 2026, 5:26 a.m.
Created at: April 9, 2026, 9 p.m.