Triple

T24246386
Position Surface form Disambiguated ID Type / Status
Subject Peine del Viento E603384 entity
Predicate architect P184 FINISHED
Object Luis Peña Ganchegui
Luis Peña Ganchegui was a prominent Spanish architect known for his influential role in modern Basque architecture and his collaborations with sculptor Eduardo Chillida.
E1812698 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: Luis Peña Ganchegui | Statement: [Peine del Viento, architect, Luis Peña Ganchegui]
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: Luis Peña Ganchegui
Triple: [Peine del Viento, architect, Luis Peña Ganchegui]
Generated description
Luis Peña Ganchegui was a prominent Spanish architect known for his influential role in modern Basque architecture and his collaborations with sculptor Eduardo Chillida.

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_69e2953f631c819097cbb421046bd417 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28b85349481909c21dacd48df7b8e completed April 29, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606e1bc188190829c97ea704d4927 completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a161feb3d908190b4b36e31cc2f5755 completed May 26, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_6a16207483b0819082e9327aa1bf63f2 completed May 26, 2026, 10:36 p.m.
Created at: April 18, 2026, 12:04 a.m.