Triple

T10546768
Position Surface form Disambiguated ID Type / Status
Subject Akita Prefecture E248838 entity
Predicate hasCity P316 FINISHED
Object Kazuno
Kazuno is a city in northern Japan known for its hot springs, traditional festivals, and mountainous rural scenery.
 E896439 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: Kazuno | Statement: [Akita Prefecture, hasCity, Kazuno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kazuno
Context triple: [Akita Prefecture, hasCity, Kazuno]
  • A. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • B. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • C. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • D. Takamori
    Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
  • E. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • 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: Kazuno
Triple: [Akita Prefecture, hasCity, Kazuno]
Generated description
Kazuno is a city in northern Japan known for its hot springs, traditional festivals, and mountainous rural scenery.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kazuno
Target entity description: Kazuno is a city in northern Japan known for its hot springs, traditional festivals, and mountainous rural scenery.
  • A. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • B. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • C. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • D. Takamori
    Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
  • E. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d20ef48190ab9f70d4ce5f2a11 completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69e2d65fc0948190af4356fc9f5004bb completed April 18, 2026, 12:54 a.m.
NEDg Description generation batch_69e2ff1ddd2c8190b31f5007f7492a4e completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e3260494bc81909e3dd4829697fb72 completed April 18, 2026, 6:34 a.m.
Created at: April 6, 2026, 12:33 p.m.