Triple

T20387326
Position Surface form Disambiguated ID Type / Status
Subject Cowboy Bebop (2021 TV series) E497991 entity
Predicate executiveProducer P7225 FINISHED
Object Shin Sasaki
Shin Sasaki is a television producer best known for serving as an executive producer on the 2021 live-action adaptation of the anime series Cowboy Bebop.
E2092986 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: Shin Sasaki | Statement: [Cowboy Bebop (2021 TV series), executiveProducer, Shin Sasaki]
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: Shin Sasaki
Triple: [Cowboy Bebop (2021 TV series), executiveProducer, Shin Sasaki]
Generated description
Shin Sasaki is a television producer best known for serving as an executive producer on the 2021 live-action adaptation of the anime series Cowboy Bebop.

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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790c935881908f901d058e6a83a9 completed April 20, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3704765f208190a18f228355529365 completed June 20, 2026, 9:21 p.m.
NEDg Description generation batch_6a370577d8e08190848ce63a9865793d completed June 20, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_6a370623291481909be4c2276969d415 completed June 20, 2026, 9:29 p.m.
Created at: April 16, 2026, 11:28 a.m.