Triple

T30489477
Position Surface form Disambiguated ID Type / Status
Subject Museo de Arte de Ponce E775817 entity
Predicate notableArtistInCollection P2487 FINISHED
Object Francisco Oller
Francisco Oller was a pioneering Puerto Rican painter associated with Impressionism, known for blending European artistic techniques with Caribbean themes and social realism.
E1918441 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: Francisco Oller | Statement: [Museo de Arte de Ponce, notableArtistInCollection, Francisco Oller]
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: Francisco Oller
Triple: [Museo de Arte de Ponce, notableArtistInCollection, Francisco Oller]
Generated description
Francisco Oller was a pioneering Puerto Rican painter associated with Impressionism, known for blending European artistic techniques with Caribbean themes and social realism.

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_69f22497f91c8190afa7165bc900accd completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68747d5cc8190a6b1f934b4dd7fa3 completed May 2, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be6745908190b854851fd12b0ab8 completed June 9, 2026, 7:19 a.m.
NEDg Description generation batch_6a27c05f8e088190b5b9e1277688a824 completed June 9, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_6a27c0c03db881909c0f3380f6a21fe5 completed June 9, 2026, 7:29 a.m.
Created at: April 29, 2026, 8:13 p.m.