Triple

T8759372
Position Surface form Disambiguated ID Type / Status
Subject Fujinami Kōji E208155 entity
Predicate givenName P17 FINISHED
Object Kōji
Kōji is a Japanese masculine given name commonly used in various kanji spellings with meanings that vary depending on the characters chosen.
 E797622 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: Kōji | Statement: [Fujinami Kōji, givenName, Kōji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kōji
Context triple: [Fujinami Kōji, givenName, Kōji]
  • A. Koichi
    Koichi is a Japanese given name commonly used for males and borne by various notable figures in fields such as science, politics, and entertainment.
  • B. Ryoji
    Ryoji is a Japanese given name commonly used for males.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • E. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • 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: Kōji
Triple: [Fujinami Kōji, givenName, Kōji]
Generated description
Kōji is a Japanese masculine given name commonly used in various kanji spellings with meanings that vary depending on the characters chosen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kōji
Target entity description: Kōji is a Japanese masculine given name commonly used in various kanji spellings with meanings that vary depending on the characters chosen.
  • A. Koichi
    Koichi is a Japanese given name commonly used for males and borne by various notable figures in fields such as science, politics, and entertainment.
  • B. Ryoji
    Ryoji is a Japanese given name commonly used for males.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • E. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • 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_69ca835cd6b08190bd7c63db92f53c86 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5df81c58819089af99306e103dbb completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69d10771c3288190860875ebcc12103e completed April 4, 2026, 12:43 p.m.
NEDg Description generation batch_69d1086f03808190896186daa5857e39 completed April 4, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_69d1090215308190beda7c0115020f5b completed April 4, 2026, 12:50 p.m.
Created at: March 30, 2026, 6:40 p.m.