Triple

T32556753

Position	Surface form	Disambiguated ID	Type / Status
Subject	The Cuphead Show!	`E832114`	entity
Predicate	voiceActor	`P1507`	FINISHED
Object	Frank Todaro Frank Todaro is an American voice actor and performer best known for his work in animation and video games, including roles in series like The Cuphead Show! and various Transformers projects.	`E2013122`	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: Frank Todaro | Statement: [The Cuphead Show!, voiceActor, Frank Todaro]

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: Frank Todaro
Triple: [The Cuphead Show!, voiceActor, Frank Todaro]

Generated description

Frank Todaro is an American voice actor and performer best known for his work in animation and video games, including roles in series like The Cuphead Show! and various Transformers projects.

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_69f34926b9848190ace47d2dd0a0de7c`	completed	April 30, 2026, 12:20 p.m.
NER	Named-entity recognition	`batch_69f6c5ffdd048190bc91cb29b9fe82eb`	completed	May 3, 2026, 3:50 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a347b901f64819090878c5d44152293`	completed	June 18, 2026, 11:13 p.m.
NEDg	Description generation	`batch_6a347c427de8819083c0a683e40f660b`	completed	June 18, 2026, 11:16 p.m.
NED2	Entity disambiguation (via description)	`batch_6a347e0a2ed48190b8648eb4406bef26`	completed	June 18, 2026, 11:23 p.m.

Created at: May 1, 2026, 1:03 a.m.