Triple

T9345506
Position Surface form Disambiguated ID Type / Status
Subject Yokosuka P1Y E224879 entity
Predicate manufacturer P490 FINISHED
Object Kawanishi
Kawanishi was a Japanese aircraft manufacturer best known for producing military seaplanes and bombers for the Imperial Japanese Navy during World War II.
 E844197 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: Kawanishi | Statement: [Yokosuka P1Y, manufacturer, Kawanishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kawanishi
Context triple: [Yokosuka P1Y, manufacturer, Kawanishi]
  • A. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka metropolitan area.
  • B. Tachikawa
    Tachikawa is a major city in western Tokyo, Japan, known as a key commercial and transportation hub of the Tama region.
  • C. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • D. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • E. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • 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: Kawanishi
Triple: [Yokosuka P1Y, manufacturer, Kawanishi]
Generated description
Kawanishi was a Japanese aircraft manufacturer best known for producing military seaplanes and bombers for the Imperial Japanese Navy during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kawanishi
Target entity description: Kawanishi was a Japanese aircraft manufacturer best known for producing military seaplanes and bombers for the Imperial Japanese Navy during World War II.
  • A. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka metropolitan area.
  • B. Tachikawa
    Tachikawa is a major city in western Tokyo, Japan, known as a key commercial and transportation hub of the Tama region.
  • C. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • D. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • E. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • 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_69ca842993248190a79ab06968994b86 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f0e2ccc8190a68f1c96c0886660 completed April 1, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2e4d5f5008190a897b3b10b172592 completed April 5, 2026, 10:40 p.m.
NEDg Description generation batch_69d2e901ade08190918aace071a616aa completed April 5, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_69d2e9906994819088fbf14ff4a614c5 completed April 5, 2026, 11 p.m.
Created at: March 30, 2026, 7:41 p.m.