Triple

T17143344
Position Surface form Disambiguated ID Type / Status
Subject Rina Satō E416024 entity
Predicate employer P7 FINISHED
Object Haikyō
Haikyō is a Japanese talent agency that manages voice actors and other performers in the entertainment industry.
E1274519 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: Haikyō | Statement: [Rina Satō, employer, Haikyō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haikyō
Context triple: [Rina Satō, employer, Haikyō]
  • A. Kiga
    Kiga is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda, near the Great Lakes region of East Africa.
  • B. Shinkyō
    Shinkyō is the Japanese name for Hsinking, the former capital city of the Japanese puppet state Manchukuo in northeastern China during the early 20th century.
  • C. Yakumo
    Yakumo is a residential neighborhood in Tokyo’s Meguro ward known for its quiet streets, schools, and proximity to parks and shopping areas.
  • D. Eikyū
    Eikyū was a Japanese era name (nengō) of the early 12th century, used during the reign of Emperor Toba.
  • E. Kōta
    Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
  • 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: Haikyō
Triple: [Rina Satō, employer, Haikyō]
Generated description
Haikyō is a Japanese talent agency that manages voice actors and other performers in the entertainment industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haikyō
Target entity description: Haikyō is a Japanese talent agency that manages voice actors and other performers in the entertainment industry.
  • A. Kiga
    Kiga is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda, near the Great Lakes region of East Africa.
  • B. Shinkyō
    Shinkyō is the Japanese name for Hsinking, the former capital city of the Japanese puppet state Manchukuo in northeastern China during the early 20th century.
  • C. Yakumo
    Yakumo is a residential neighborhood in Tokyo’s Meguro ward known for its quiet streets, schools, and proximity to parks and shopping areas.
  • D. Eikyū
    Eikyū was a Japanese era name (nengō) of the early 12th century, used during the reign of Emperor Toba.
  • E. Kōta
    Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d73c3c81908b875023bb925edb completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01d27638ec8190a125ee8e02086035 completed May 11, 2026, 12:58 p.m.
NEDg Description generation batch_6a01d36fcfd081908b85e5bafb3eda4e completed May 11, 2026, 1:02 p.m.
NED2 Entity disambiguation (via description) batch_6a01d3ca97b88190800530c80bd5dff0 completed May 11, 2026, 1:04 p.m.
Created at: April 10, 2026, 5:36 a.m.