Triple

T15992190
Position Surface form Disambiguated ID Type / Status
Subject Pops Racer E387859 entity
Predicate createdBy P806 FINISHED
Object Tatsuo Yoshida
Tatsuo Yoshida was a Japanese manga artist and animator best known as the creator of the classic racing series "Speed Racer" and co-founder of the influential studio Tatsunoko Production.
E2043449 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: Tatsuo Yoshida | Statement: [Pops Racer, createdBy, Tatsuo Yoshida]
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: Tatsuo Yoshida
Triple: [Pops Racer, createdBy, Tatsuo Yoshida]
Generated description
Tatsuo Yoshida was a Japanese manga artist and animator best known as the creator of the classic racing series "Speed Racer" and co-founder of the influential studio Tatsunoko Production.

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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157844ed881908b42bfc1bb740d4e completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3538e60ed481908835cc9a4ac5996d completed June 19, 2026, 12:41 p.m.
NEDg Description generation batch_6a3539d6f5448190aee35547822a99ff completed June 19, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_6a353abc2f7c8190bb5843c25bb84256 completed June 19, 2026, 12:49 p.m.
Created at: April 10, 2026, 4:54 a.m.