Triple

T35623185
Position Surface form Disambiguated ID Type / Status
Subject Bertie E1029373 entity
Predicate duoWith P45764 FINISHED
Object Hubie
Hubie is a character best known as one half of the animated comedy duo Bertie and Hubie, often portrayed as a pair of bumbling penguins in classic cartoons.
E2149223 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: Hubie | Statement: [Bertie, duoWith, Hubie]
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: Hubie
Triple: [Bertie, duoWith, Hubie]
Generated description
Hubie is a character best known as one half of the animated comedy duo Bertie and Hubie, often portrayed as a pair of bumbling penguins in classic cartoons.

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_69f76e0709408190bbe322bf1707ef6b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ef3d120819084fb33df17a73b15 completed May 3, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a386848ed6c819084daa8bb1f920a82 completed June 21, 2026, 10:40 p.m.
NEDg Description generation batch_6a386913196c81908274a2e909d943b8 completed June 21, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a3869ecb09c8190bffe477099dcc2cf completed June 21, 2026, 10:47 p.m.
Created at: May 3, 2026, 4:05 p.m.