Triple

T26182757
Position Surface form Disambiguated ID Type / Status
Subject Paper Mario: Color Splash E654730 entity
Predicate soundtrackComposer P32102 FINISHED
Object Tetsundo Okubo
Tetsundo Okubo is a video game music composer known for his work on Nintendo titles, including contributing to the soundtrack of Paper Mario: Color Splash.
E2283774 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: Tetsundo Okubo | Statement: [Paper Mario: Color Splash, soundtrackComposer, Tetsundo Okubo]
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: Tetsundo Okubo
Triple: [Paper Mario: Color Splash, soundtrackComposer, Tetsundo Okubo]
Generated description
Tetsundo Okubo is a video game music composer known for his work on Nintendo titles, including contributing to the soundtrack of Paper Mario: Color Splash.

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_69ee5b469bc081908fe486453fdad810 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c71dfb48190a3f0ab63ecadbdfa completed May 2, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a42e078c0848190b078c9c41fc66b17 completed June 29, 2026, 9:15 p.m.
NEDg Description generation batch_6a42e148d1708190b1b5bef0ef2b9078 completed June 29, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a42ec8ba09c819095262fda3589b6ad completed June 29, 2026, 10:07 p.m.
Created at: April 26, 2026, 8:41 p.m.