Triple

T8624591
Position Surface form Disambiguated ID Type / Status
Subject Imamura Shohei E204251 entity
Predicate workedAt P7 FINISHED
Object Nikkatsu
Nikkatsu is one of Japan’s oldest and most influential film studios, known for producing a wide range of popular and auteur cinema throughout the 20th century.
 E747495 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: Nikkatsu | Statement: [Imamura Shohei, workedAt, Nikkatsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nikkatsu
Context triple: [Imamura Shohei, workedAt, Nikkatsu]
  • A. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • B. 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.
  • C. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • D. Takasaki
    Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
  • E. Ōtsu
    Ōtsu is a Japanese city on the southwestern shore of Lake Biwa, known for its historic temples, scenic lake views, and role as a transportation hub near Kyoto.
  • 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: Nikkatsu
Triple: [Imamura Shohei, workedAt, Nikkatsu]
Generated description
Nikkatsu is one of Japan’s oldest and most influential film studios, known for producing a wide range of popular and auteur cinema throughout the 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nikkatsu
Target entity description: Nikkatsu is one of Japan’s oldest and most influential film studios, known for producing a wide range of popular and auteur cinema throughout the 20th century.
  • A. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • B. 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.
  • C. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • D. Takasaki
    Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
  • E. Ōtsu
    Ōtsu is a Japanese city on the southwestern shore of Lake Biwa, known for its historic temples, scenic lake views, and role as a transportation hub near Kyoto.
  • 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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4728360c8190b5e600596cbced0c completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbe6a7e48190a166a31dccd8ac16 completed April 2, 2026, 6:56 p.m.
NEDg Description generation batch_69cebe299de881909dcbb37b2b718201 completed April 2, 2026, 7:06 p.m.
NED2 Entity disambiguation (via description) batch_69cebedb7f0c8190be98ffec07ce6fbc completed April 2, 2026, 7:09 p.m.
Created at: March 30, 2026, 6:26 p.m.