Triple

T28895097
Position Surface form Disambiguated ID Type / Status
Subject Blaze the Cat E732815 entity
Predicate voiceActorEnglish P83203 FINISHED
Object Erica Schroeder
Erica Schroeder is an American voice actress known for her work in anime, video games, and animated series, including roles in franchises like Pokémon and Yu-Gi-Oh!.
E1893461 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: Erica Schroeder | Statement: [Blaze the Cat, voiceActorEnglish, Erica Schroeder]
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: Erica Schroeder
Triple: [Blaze the Cat, voiceActorEnglish, Erica Schroeder]
Generated description
Erica Schroeder is an American voice actress known for her work in anime, video games, and animated series, including roles in franchises like Pokémon and Yu-Gi-Oh!.

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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65aa2c5fc8190a74ea45c30e714d4 completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721cc41cc819096356c4ac956f8f7 completed June 8, 2026, 8:10 p.m.
NEDg Description generation batch_6a2722966b2881909134a0135c1db6ee completed June 8, 2026, 8:14 p.m.
NED2 Entity disambiguation (via description) batch_6a272344de1c819093cc8b8387452668 completed June 8, 2026, 8:17 p.m.
Created at: April 28, 2026, 7:58 a.m.