Triple

T32016606
Position Surface form Disambiguated ID Type / Status
Subject Oakey Oaks E817559 entity
Predicate partOf P40 FINISHED
Object fictional world of Chicken Little
The fictional world of Chicken Little is a whimsical, anthropomorphic animal town setting from the Disney animated film where everyday life and cosmic-scale events comically collide.
E1989363 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: fictional world of Chicken Little | Statement: [Oakey Oaks, partOf, fictional world of Chicken Little]
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: fictional world of Chicken Little
Triple: [Oakey Oaks, partOf, fictional world of Chicken Little]
Generated description
The fictional world of Chicken Little is a whimsical, anthropomorphic animal town setting from the Disney animated film where everyday life and cosmic-scale events comically collide.

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_69f348f9e5d081908cc3f57c4942af52 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b43ae168819098c9774e3634b47a completed May 3, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ed4e74c20819086ff8e4086dd70bd completed June 14, 2026, 4:20 p.m.
NEDg Description generation batch_6a2ed614bb04819081528a6e61d52a73 completed June 14, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_6a2ed803dd348190acb0253e6c8e98dc completed June 14, 2026, 4:34 p.m.
Created at: May 1, 2026, 12:16 a.m.