Triple

T28226577
Position Surface form Disambiguated ID Type / Status
Subject The Magic Christian E711602 entity
Predicate mainCharacter P1183 FINISHED
Object Guy Grand
Guy Grand is an eccentric billionaire anti-hero from Terry Southern’s satirical novel and its film adaptation, known for staging elaborate pranks to expose human greed and hypocrisy.
E1807583 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: Guy Grand | Statement: [The Magic Christian, mainCharacter, Guy Grand]
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: Guy Grand
Triple: [The Magic Christian, mainCharacter, Guy Grand]
Generated description
Guy Grand is an eccentric billionaire anti-hero from Terry Southern’s satirical novel and its film adaptation, known for staging elaborate pranks to expose human greed and hypocrisy.

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_69efb51dfb048190ada79b745c33b363 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f64384644c81909b429ac2a5c34999 completed May 2, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6c934288190960d5cfab649bb3b completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15e8b61a208190a39c169833b17110 completed May 26, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_6a15e92e502081908c8ad21a09bfefb9 completed May 26, 2026, 6:40 p.m.
Created at: April 27, 2026, 10:50 p.m.