Triple

T30736641
Position Surface form Disambiguated ID Type / Status
Subject Gerard David E782568 entity
Predicate influenced P9 FINISHED
Object Adriaen Isenbrandt
Adriaen Isenbrandt was a Flemish Renaissance painter active in Bruges, known for his religious panels and refined, detailed style characteristic of the Northern Renaissance.
E1986338 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: Adriaen Isenbrandt | Statement: [Gerard David, influenced, Adriaen Isenbrandt]
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: Adriaen Isenbrandt
Triple: [Gerard David, influenced, Adriaen Isenbrandt]
Generated description
Adriaen Isenbrandt was a Flemish Renaissance painter active in Bruges, known for his religious panels and refined, detailed style characteristic of the Northern Renaissance.

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_69f224aeb1588190897d395e8ed2acb8 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68ee76a3c819096e4d548a9ca22da completed May 2, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb11658508190a5e92e9fb644127c completed June 14, 2026, 1:48 p.m.
NEDg Description generation batch_6a2eb2a1118c8190a53358c3bd85f79c completed June 14, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a2eb2f4a710819098442ba2198aecf6 completed June 14, 2026, 1:56 p.m.
Created at: April 29, 2026, 8:37 p.m.