Triple

T26319684
Position Surface form Disambiguated ID Type / Status
Subject Musée Soulages E662070 entity
Predicate architect P184 FINISHED
Object Ramon Vilalta
Ramon Vilalta is a Spanish architect, co-founder of the RCR Arquitectes studio, renowned for his minimalist, landscape-integrated designs and recipient of the Pritzker Architecture Prize.
E1725066 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: Ramon Vilalta | Statement: [Musée Soulages, architect, Ramon Vilalta]
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: Ramon Vilalta
Triple: [Musée Soulages, architect, Ramon Vilalta]
Generated description
Ramon Vilalta is a Spanish architect, co-founder of the RCR Arquitectes studio, renowned for his minimalist, landscape-integrated designs and recipient of the Pritzker Architecture Prize.

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_69ee812e73048190aae587f1d51e5a06 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60f2a5a108190879bc2acdc868dad completed May 2, 2026, 2:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aea847d48190a6bdfafb403df535 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11afcce63c8190ac822c630de91480 completed May 23, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a11b08396c8819094b627b21872f43b completed May 23, 2026, 1:49 p.m.
Created at: April 26, 2026, 10:27 p.m.