Triple

T1604066
Position Surface form Disambiguated ID Type / Status
Subject Ryūnosuke Akutagawa E34457 entity
Predicate notableWork P4 FINISHED
Object Kappa
Kappa is a satirical 1927 novella by Ryūnosuke Akutagawa that critiques modern Japanese society through the perspective of a man who finds himself in a bizarre world inhabited by mythical kappa creatures.
 E182908 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: Kappa | Statement: [Ryūnosuke Akutagawa, notableWork, Kappa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kappa
Context triple: [Ryūnosuke Akutagawa, notableWork, Kappa]
  • A. Kappa
    Kappa is an Italian sportswear brand known for producing athletic apparel and sponsoring numerous football teams and athletes worldwide.
  • B. Zeta
    Zeta is a historical region in present-day Montenegro that once formed a medieval principality and early state precursor to the country.
  • C. Zeta
    Zeta is the sixth letter of the Greek alphabet, corresponding roughly to the English "z" sound.
  • D. Iota
    Iota is the ninth letter of the Greek alphabet, historically representing a short "i" sound and giving rise to the Latin letter I.
  • E. Upsilon
    Upsilon is a letter of the Greek alphabet that historically represented a "u" or "y" vowel sound and is used in various scientific and mathematical contexts.
  • 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: Kappa
Triple: [Ryūnosuke Akutagawa, notableWork, Kappa]
Generated description
Kappa is a satirical 1927 novella by Ryūnosuke Akutagawa that critiques modern Japanese society through the perspective of a man who finds himself in a bizarre world inhabited by mythical kappa creatures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kappa
Target entity description: Kappa is a satirical 1927 novella by Ryūnosuke Akutagawa that critiques modern Japanese society through the perspective of a man who finds himself in a bizarre world inhabited by mythical kappa creatures.
  • A. Kappa
    Kappa is an Italian sportswear brand known for producing athletic apparel and sponsoring numerous football teams and athletes worldwide.
  • B. Zeta
    Zeta is a historical region in present-day Montenegro that once formed a medieval principality and early state precursor to the country.
  • C. Zeta
    Zeta is the sixth letter of the Greek alphabet, corresponding roughly to the English "z" sound.
  • D. Iota
    Iota is the ninth letter of the Greek alphabet, historically representing a short "i" sound and giving rise to the Latin letter I.
  • E. Upsilon
    Upsilon is a letter of the Greek alphabet that historically represented a "u" or "y" vowel sound and is used in various scientific and mathematical contexts.
  • 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9094f96ec819090286c21b3dfddd5 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51bcdebc81909520786c560598b6 completed March 8, 2026, 10:38 a.m.
NEDg Description generation batch_69ad52c9e3e8819094a91530ec91541c completed March 8, 2026, 10:43 a.m.
NED2 Entity disambiguation (via description) batch_69ad5330a9048190bd07e118c09d7eae completed March 8, 2026, 10:45 a.m.
Created at: March 4, 2026, 7:28 p.m.