Triple

T27936437
Position Surface form Disambiguated ID Type / Status
Subject Roller Coaster Rabbit E700624 entity
Predicate voiceOf P2181 FINISHED
Object Lou Hirsch as Baby Herman
Lou Hirsch as Baby Herman is the voice performance of the foul-mouthed, cigar-chomping infant cartoon character Baby Herman in the animated short "Roller Coaster Rabbit."
E1797498 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: Lou Hirsch as Baby Herman | Statement: [Roller Coaster Rabbit, voiceOf, Lou Hirsch as Baby Herman]
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: Lou Hirsch as Baby Herman
Triple: [Roller Coaster Rabbit, voiceOf, Lou Hirsch as Baby Herman]
Generated description
Lou Hirsch as Baby Herman is the voice performance of the foul-mouthed, cigar-chomping infant cartoon character Baby Herman in the animated short "Roller Coaster Rabbit."

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_69ef6a5028108190a14696d9821dde49 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f63aa0607c8190bff3c752d6b84441 completed May 2, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13115b94c88190b15cf581a310d778 completed May 24, 2026, 2:55 p.m.
NEDg Description generation batch_6a13127b3a688190b36805e60f2db695 completed May 24, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a13138f4e508190b50a250487666a14 completed May 24, 2026, 3:04 p.m.
Created at: April 27, 2026, 7:13 p.m.