Triple

T25347575
Position Surface form Disambiguated ID Type / Status
Subject The Counterfeiters E635591 entity
Predicate hasCharacter P2308 FINISHED
Object Georges Molinier
Georges Molinier is a character in André Gide’s novel "The Counterfeiters," involved in the book’s intricate web of moral ambiguity, artistic creation, and personal relationships.
E2290585 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: Georges Molinier | Statement: [The Counterfeiters, hasCharacter, Georges Molinier]
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: Georges Molinier
Triple: [The Counterfeiters, hasCharacter, Georges Molinier]
Generated description
Georges Molinier is a character in André Gide’s novel "The Counterfeiters," involved in the book’s intricate web of moral ambiguity, artistic creation, and personal relationships.

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_69e75a9ac5d881909387ed766e20cd47 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f498bd7e648190855fcf9e2ee4c762 completed May 1, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5be47d9cf88190bf5598c9753518a5 completed July 18, 2026, 8:39 p.m.
NEDg Description generation batch_6a5be4fe78d8819089556c13c3750e3c completed July 18, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_6a5be54e1a688190b5981f7ca4b75e68 completed July 18, 2026, 8:42 p.m.
Created at: April 21, 2026, 1:34 p.m.