Triple

T22109020
Position Surface form Disambiguated ID Type / Status
Subject Kenzo Kitakata E546365 entity
Predicate notableWork P4 FINISHED
Object Ashes
"Ashes" is a hardboiled Japanese crime novel by Kenzo Kitakata, known for its gritty realism and exploration of the criminal underworld.
E1518447 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: Ashes | Statement: [Kenzo Kitakata, notableWork, Ashes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashes
Context triple: [Kenzo Kitakata, notableWork, Ashes]
  • A. Ashes
    Ashes is an 1894 painting by Norwegian artist Edvard Munch that depicts a tense, emotionally charged scene between a man and a woman in a forest, reflecting themes of despair and fractured relationships.
  • B. Ashes
    "Ashes" is a film directed by Mat Whitecross, known for its gritty, character-driven storytelling.
  • C. Ashes
    "Ashes" is the debut studio album by American electronic music producer Illenium, known for its melodic bass sound and emotionally driven tracks.
  • D. The Ashes
    The Ashes is a historic Test cricket series played between England and Australia and is one of the sport’s most famous and fiercely contested rivalries.
  • E. Ashes in the Fall
    "Ashes in the Fall" is a politically charged rap metal song by Rage Against the Machine from their influential album "The Battle of Los Angeles."
  • 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: Ashes
Triple: [Kenzo Kitakata, notableWork, Ashes]
Generated description
"Ashes" is a hardboiled Japanese crime novel by Kenzo Kitakata, known for its gritty realism and exploration of the criminal underworld.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ashes
Target entity description: "Ashes" is a hardboiled Japanese crime novel by Kenzo Kitakata, known for its gritty realism and exploration of the criminal underworld.
  • A. Ashes
    Ashes is an 1894 painting by Norwegian artist Edvard Munch that depicts a tense, emotionally charged scene between a man and a woman in a forest, reflecting themes of despair and fractured relationships.
  • B. Ashes
    "Ashes" is a film directed by Mat Whitecross, known for its gritty, character-driven storytelling.
  • C. Ashes
    "Ashes" is the debut studio album by American electronic music producer Illenium, known for its melodic bass sound and emotionally driven tracks.
  • D. The Ashes
    The Ashes is a historic Test cricket series played between England and Australia and is one of the sport’s most famous and fiercely contested rivalries.
  • E. Ashes in the Fall
    "Ashes in the Fall" is a politically charged rap metal song by Rage Against the Machine from their influential album "The Battle of Los Angeles."
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1291b9c988190b3ddd06d1f40dc78 completed April 28, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a87ac12e881909ba2c0de6f3b26f5 completed May 18, 2026, 3:29 a.m.
NEDg Description generation batch_6a0a88e654ac8190a0e77e946bd9722b completed May 18, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_6a0a8966298c8190a0d0e7d2b6eacdb4 completed May 18, 2026, 3:37 a.m.
Created at: April 16, 2026, 8:30 p.m.