Triple

T35477514
Position Surface form Disambiguated ID Type / Status
Subject Madame Adelaide Bonfamille E1025375 entity
Predicate ownsPet P8711 FINISHED
Object Marie
Marie is the white-furred, pink-bowed kitten from Disney's "The Aristocats," known for her prim, ladylike demeanor and musical talents.
E2134231 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: Marie | Statement: [Madame Adelaide Bonfamille, ownsPet, Marie]
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: Marie
Triple: [Madame Adelaide Bonfamille, ownsPet, Marie]
Generated description
Marie is the white-furred, pink-bowed kitten from Disney's "The Aristocats," known for her prim, ladylike demeanor and musical talents.

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_69f76dfadba0819083456aadcd6864ea completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796e951b08190854327f83932c83c completed May 3, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a2977a08190bd16b71256f938d2 completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384af0370c8190b49b96626cfb98c2 completed June 21, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a384b839a308190a63708ae678946da completed June 21, 2026, 8:37 p.m.
Created at: May 3, 2026, 4:04 p.m.