Triple

T13992464
Position Surface form Disambiguated ID Type / Status
Subject 加藤友三郎 E336614 entity
Predicate givenName P17 FINISHED
Object 友三郎
友三郎 is a Japanese masculine given name historically borne by notable figures such as statesmen and military officers.
E1072960 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: 友三郎 | Statement: [加藤友三郎, givenName, 友三郎]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 友三郎
Context triple: [加藤友三郎, givenName, 友三郎]
  • A. 平八郎
    平八郎 is a Japanese masculine given name, often associated with historical and military figures.
  • B. 二子玉川
    二子玉川 is a riverside commercial and residential district in Tokyo known for its large shopping complexes, stylish cafes, and family-friendly urban development along the Tama River.
  • C. 純一郎
    純一郎 is a masculine Japanese given name typically written with kanji conveying meanings such as “pure” and “first son.”
  • D. 太郎
    太郎 is a common Japanese male given name, traditionally used for the eldest son and written with kanji meaning "great" and "son."
  • E. 健太郎
    健太郎 is a common Japanese masculine given name that can be written with various kanji combinations, often conveying meanings related to health, strength, and boyhood.
  • 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: 友三郎
Triple: [加藤友三郎, givenName, 友三郎]
Generated description
友三郎 is a Japanese masculine given name historically borne by notable figures such as statesmen and military officers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 友三郎
Target entity description: 友三郎 is a Japanese masculine given name historically borne by notable figures such as statesmen and military officers.
  • A. 平八郎
    平八郎 is a Japanese masculine given name, often associated with historical and military figures.
  • B. 二子玉川
    二子玉川 is a riverside commercial and residential district in Tokyo known for its large shopping complexes, stylish cafes, and family-friendly urban development along the Tama River.
  • C. 純一郎
    純一郎 is a masculine Japanese given name typically written with kanji conveying meanings such as “pure” and “first son.”
  • D. 太郎
    太郎 is a common Japanese male given name, traditionally used for the eldest son and written with kanji meaning "great" and "son."
  • E. 健太郎
    健太郎 is a common Japanese masculine given name that can be written with various kanji combinations, often conveying meanings related to health, strength, and boyhood.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2eb3b5d881909f15a1e08bb202f3 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac98ca448190b585ef69a4e4bfca completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbae8f83f481909ac16d4bb66ea79d completed May 6, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69fbaf71ad648190b9128851ba62590e completed May 6, 2026, 9:15 p.m.
Created at: April 9, 2026, 10:19 p.m.