Triple

T35105098
Position Surface form Disambiguated ID Type / Status
Subject Grandet family E1013129 entity
Predicate hasMember P10 FINISHED
Object Charles Grandet
Charles Grandet is a character in Honoré de Balzac’s novel "Eugénie Grandet," known as the Parisian cousin whose arrival profoundly affects the life and fortunes of the Grandet family.
E2133947 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: Charles Grandet | Statement: [Grandet family, hasMember, Charles Grandet]
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: Charles Grandet
Triple: [Grandet family, hasMember, Charles Grandet]
Generated description
Charles Grandet is a character in Honoré de Balzac’s novel "Eugénie Grandet," known as the Parisian cousin whose arrival profoundly affects the life and fortunes of the Grandet family.

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_69f76dd556248190808b4c4f43debebb completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78c0b95448190b35fe105e6dd8eab completed May 3, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380f9114d48190a6b48e4e7bbc81be completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a3813552a208190b8e37c1f109aa589 completed June 21, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_6a3813f1f984819081860c509642ee1d completed June 21, 2026, 4:40 p.m.
Created at: May 3, 2026, 4:01 p.m.