Triple

T17911032
Position Surface form Disambiguated ID Type / Status
Subject Sailor Moon E447818 entity
Predicate animeDirector P85631 FINISHED
Object Junichi Sato
Junichi Sato is a Japanese anime director best known for his work on influential magical girl and slice-of-life series, including early episodes of Sailor Moon and the Aria franchise.
E2291092 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: Junichi Sato | Statement: [Sailor Moon, animeDirector, Junichi Sato]
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: Junichi Sato
Triple: [Sailor Moon, animeDirector, Junichi Sato]
Generated description
Junichi Sato is a Japanese anime director best known for his work on influential magical girl and slice-of-life series, including early episodes of Sailor Moon and the Aria franchise.

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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49ea017d081908be850a39edf601f completed April 19, 2026, 9:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c25a87ffc8190828493bdee06890f completed July 19, 2026, 1:17 a.m.
NEDg Description generation batch_6a5c26d6c7d48190a16c765b56176156 completed July 19, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a5c2b09bd648190816ea37cf33623d5 completed July 19, 2026, 1:40 a.m.
Created at: April 10, 2026, 10:19 a.m.