Triple

T29728007
Position Surface form Disambiguated ID Type / Status
Subject Maison&Objet E752235 entity
Predicate hasComponent P35 FINISHED
Object Maison&Objet digital platform
Maison&Objet digital platform is an online extension of the Maison&Objet design and lifestyle trade fair that connects brands, buyers, and professionals through virtual showcases, networking, and curated content.
E752235 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: Maison&Objet digital platform | Statement: [Maison&Objet, hasComponent, Maison&Objet digital platform]
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: Maison&Objet digital platform
Triple: [Maison&Objet, hasComponent, Maison&Objet digital platform]
Generated description
Maison&Objet digital platform is an online extension of the Maison&Objet design and lifestyle trade fair that connects brands, buyers, and professionals through virtual showcases, networking, and curated content.

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_69f0d62a36a88190bf860f00da433ff8 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f673008bb081909623ca50205dc0a8 completed May 2, 2026, 9:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa83fdc8819095a1bfdf345b8020 completed June 8, 2026, 11:41 a.m.
NEDg Description generation batch_6a26b058df8c819092e2cd55bf17a5cb completed June 8, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a26b495ec448190ac88779dae9a72dc completed June 8, 2026, 12:24 p.m.
Created at: April 28, 2026, 7:40 p.m.