Triple

T28327417
Position Surface form Disambiguated ID Type / Status
Subject Kenner Products E717449 entity
Predicate notableProduct P1448 FINISHED
Object Care Bears toys
Care Bears toys are a popular line of colorful, plush teddy bears, each with a unique belly symbol and personality, originally created in the 1980s and beloved by children for their themes of caring and friendship.
E1814487 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: Care Bears toys | Statement: [Kenner Products, notableProduct, Care Bears toys]
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: Care Bears toys
Triple: [Kenner Products, notableProduct, Care Bears toys]
Generated description
Care Bears toys are a popular line of colorful, plush teddy bears, each with a unique belly symbol and personality, originally created in the 1980s and beloved by children for their themes of caring and friendship.

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_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f6493036f4819095f94ef6457dd35d completed May 2, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627b32b148190a52cb197d67bf516 completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a1628bdc5ac81909d5f7dbdfad7934c completed May 26, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_6a16294f42508190aac4e3617131dafe completed May 26, 2026, 11:14 p.m.
Created at: April 28, 2026, 12:29 a.m.