Triple

T25827468
Position Surface form Disambiguated ID Type / Status
Subject Beverly Cleary’s Klickitat Street neighborhood E650572 entity
Predicate notableCharacter P1481 FINISHED
Object Ribsy
Ribsy is the beloved, adventurous dog from Beverly Cleary’s Klickitat Street books, best known as Henry Huggins’s loyal pet and a central figure in several of her children’s stories.
E1697103 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: Ribsy | Statement: [Beverly Cleary’s Klickitat Street neighborhood, notableCharacter, Ribsy]
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: Ribsy
Triple: [Beverly Cleary’s Klickitat Street neighborhood, notableCharacter, Ribsy]
Generated description
Ribsy is the beloved, adventurous dog from Beverly Cleary’s Klickitat Street books, best known as Henry Huggins’s loyal pet and a central figure in several of her children’s stories.

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_69e7ab37438081908f1ccf6284839520 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f60196db508190956c0b7cbc66d4df completed May 2, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da2807ec81908e6bdff8926813ae completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10dd8a06b881909f8a9ca5d7d77576 completed May 22, 2026, 10:49 p.m.
NED2 Entity disambiguation (via description) batch_6a10de47e1f0819082aae48923ded2c1 completed May 22, 2026, 10:52 p.m.
Created at: April 22, 2026, 7:37 a.m.