Triple

T34549548
Position Surface form Disambiguated ID Type / Status
Subject Palacio de la Magdalena E887023 entity
Predicate architect P184 FINISHED
Object Javier González de Riancho
Javier González de Riancho was a Spanish architect best known for his influential early 20th-century works in Santander, Spain.
E2125692 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: Javier González de Riancho | Statement: [Palacio de la Magdalena, architect, Javier González de Riancho]
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: Javier González de Riancho
Triple: [Palacio de la Magdalena, architect, Javier González de Riancho]
Generated description
Javier González de Riancho was a Spanish architect best known for his influential early 20th-century works in Santander, Spain.

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_69f349cff89081908f91e0b064f4833e completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72024a3348190b5e21ba600e64bb4 completed May 3, 2026, 10:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37cfcdd88c81909ee118f17a5fb1cc completed June 21, 2026, 11:49 a.m.
NEDg Description generation batch_6a37d07ba708819081b552b8a69313e5 completed June 21, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37d1935d9881909cee3755fec2d996 completed June 21, 2026, 11:57 a.m.
Created at: May 1, 2026, 2:02 a.m.