Triple

T18739188
Position Surface form Disambiguated ID Type / Status
Subject The Legend of Zelda: Twilight Princess E458245 entity
Predicate artist P184 FINISHED
Object Satoru Takizawa
Satoru Takizawa is a Japanese video game artist and designer best known for his work on Nintendo’s The Legend of Zelda series, including Twilight Princess.
E2292215 NE FINISHED

How this triple was built (2 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: Satoru Takizawa | Statement: [The Legend of Zelda: Twilight Princess, artist, Satoru Takizawa]
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: Satoru Takizawa
Triple: [The Legend of Zelda: Twilight Princess, artist, Satoru Takizawa]
Generated description
Satoru Takizawa is a Japanese video game artist and designer best known for his work on Nintendo’s The Legend of Zelda series, including Twilight Princess.

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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5768ca990819098102f8522ce401f completed April 20, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cd53a5e308190882815ce91e0eacc completed July 19, 2026, 1:46 p.m.
NEDg Description generation batch_6a5cd5ab7a0c8190aebf4108f4400ef6 completed July 19, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_6a5cd627f58c8190b1511b8ba858f69a completed July 19, 2026, 1:50 p.m.
Created at: April 10, 2026, 11:51 a.m.