Triple

T4306825
Position Surface form Disambiguated ID Type / Status
Subject Yokosuka D4Y E99973 entity
Predicate alliedReportingName P19661 FINISHED
Object Judy
Judy was the Allied reporting name for the Japanese Yokosuka D4Y carrier-based dive bomber used by the Imperial Japanese Navy during World War II.
 E434069 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: Judy | Statement: [Yokosuka D4Y, alliedReportingName, Judy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Judy
Context triple: [Yokosuka D4Y, alliedReportingName, Judy]
  • A. Judy
    "Judy" is a 2019 biographical drama film in which Renée Zellweger portrays legendary entertainer Judy Garland during her final years, a role that earned her widespread acclaim and major acting awards.
  • B. Judy
    Judy is a character in the 2014 British apocalyptic comedy film "The Second Coming."
  • C. Audrey
    Audrey is a kind-hearted, nature-loving girl in the 2012 animated film "The Lorax" whose dream of seeing real trees inspires the protagonist’s quest.
  • D. Edie
    Edie is a 2017 British drama film starring Sheila Hancock as an elderly woman who embarks on a life-changing mountain-climbing adventure in the Scottish Highlands.
  • E. Janet
    Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • 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: Judy
Triple: [Yokosuka D4Y, alliedReportingName, Judy]
Generated description
Judy was the Allied reporting name for the Japanese Yokosuka D4Y carrier-based dive bomber used by the Imperial Japanese Navy during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Judy
Target entity description: Judy was the Allied reporting name for the Japanese Yokosuka D4Y carrier-based dive bomber used by the Imperial Japanese Navy during World War II.
  • A. Judy
    "Judy" is a 2019 biographical drama film in which Renée Zellweger portrays legendary entertainer Judy Garland during her final years, a role that earned her widespread acclaim and major acting awards.
  • B. Judy
    Judy is a character in the 2014 British apocalyptic comedy film "The Second Coming."
  • C. Audrey
    Audrey is a kind-hearted, nature-loving girl in the 2012 animated film "The Lorax" whose dream of seeing real trees inspires the protagonist’s quest.
  • D. Edie
    Edie is a 2017 British drama film starring Sheila Hancock as an elderly woman who embarks on a life-changing mountain-climbing adventure in the Scottish Highlands.
  • E. Janet
    Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350bb78cc8190a850aca47d8711cf completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db8e40f0819082a15006a1578405 completed March 14, 2026, 10:05 p.m.
NEDg Description generation batch_69b5dc3d81a08190b29b633009fab4ff completed March 14, 2026, 10:07 p.m.
NED2 Entity disambiguation (via description) batch_69b5e04f356c81909e3f6f2c865e0f99 completed March 14, 2026, 10:25 p.m.
Created at: March 12, 2026, 11:09 p.m.