Triple

T27126290
Position Surface form Disambiguated ID Type / Status
Subject Musée Antoine Vivenel E681440 entity
Predicate locatedInBuilding P40 FINISHED
Object Hôtel de Songeons-Bicquilley
The Hôtel de Songeons-Bicquilley is a historic hôtel particulier in Compiègne, France, notable for housing the Musée Antoine Vivenel and exemplifying refined French urban architecture.
 E1757631 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: Hôtel de Songeons-Bicquilley | Statement: [Musée Antoine Vivenel, locatedInBuilding, Hôtel de Songeons-Bicquilley]
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: Hôtel de Songeons-Bicquilley
Triple: [Musée Antoine Vivenel, locatedInBuilding, Hôtel de Songeons-Bicquilley]
Generated description
The Hôtel de Songeons-Bicquilley is a historic hôtel particulier in Compiègne, France, notable for housing the Musée Antoine Vivenel and exemplifying refined French urban architecture.

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_69eefacbcc2081909ebf00daa23f1981 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6244851b88190b1995ab29dd2e30b completed May 2, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12481925308190a0a239bf011ed315 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a1248bb58a48190ae84e7b538b10503 completed May 24, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a124973e3c88190898b0cece69419b3 completed May 24, 2026, 12:42 a.m.
Created at: April 27, 2026, 9:01 a.m.