Triple

T28312625
Position Surface form Disambiguated ID Type / Status
Subject Musée Condé E714038 entity
Predicate hasSection P35 FINISHED
Object Galerie de Psyché
Galerie de Psyché is an ornate gallery within the Musée Condé at the Château de Chantilly, renowned for its mythological decorations and artworks depicting the story of Psyche.
E1810524 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: Galerie de Psyché | Statement: [Musée Condé, hasSection, Galerie de Psyché]
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: Galerie de Psyché
Triple: [Musée Condé, hasSection, Galerie de Psyché]
Generated description
Galerie de Psyché is an ornate gallery within the Musée Condé at the Château de Chantilly, renowned for its mythological decorations and artworks depicting the story of Psyche.

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_69efb5256afc8190b9322d25c3ae6320 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f644e3dcb08190a8002133c931cc20 completed May 2, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16073c9f8c8190b1ec9f3a82354f41 completed May 26, 2026, 8:49 p.m.
NEDg Description generation batch_6a1613d441c081909621186cd6fe1562 completed May 26, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a16141b8d348190b6ed85f7427c7a62 completed May 26, 2026, 9:43 p.m.
Created at: April 27, 2026, 11:41 p.m.