Triple

T36412510
Position Surface form Disambiguated ID Type / Status
Subject Only Yesterday (2016 English dub) E896917 entity
Predicate voiceCast P18510 FINISHED
Object Mona Marshall
Mona Marshall is an American voice actress known for her extensive work in English-dubbed anime and animation, including roles in series like South Park and numerous Studio Ghibli films.
E2181526 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: Mona Marshall | Statement: [Only Yesterday (2016 English dub), voiceCast, Mona Marshall]
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: Mona Marshall
Triple: [Only Yesterday (2016 English dub), voiceCast, Mona Marshall]
Generated description
Mona Marshall is an American voice actress known for her extensive work in English-dubbed anime and animation, including roles in series like South Park and numerous Studio Ghibli films.

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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd3071cc81908e67378ad0e31a64 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b44cd7fc8190a449fd27e7199643 completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39b61fe0f8819083be78e09186c2d0 completed June 22, 2026, 10:24 p.m.
NED2 Entity disambiguation (via description) batch_6a39b6bb50a88190ad123d3823585299 completed June 22, 2026, 10:27 p.m.
Created at: May 3, 2026, 4:10 p.m.