Triple

T26773547
Position Surface form Disambiguated ID Type / Status
Subject Petrus Christus E670050 entity
Predicate memberOf P10 FINISHED
Object Guild of Saint Luke in Bruges
The Guild of Saint Luke in Bruges was a powerful medieval and early Renaissance artists’ and craftsmen’s guild that regulated the city’s painting and related visual arts professions.
E1743640 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: Guild of Saint Luke in Bruges | Statement: [Petrus Christus, memberOf, Guild of Saint Luke in Bruges]
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: Guild of Saint Luke in Bruges
Triple: [Petrus Christus, memberOf, Guild of Saint Luke in Bruges]
Generated description
The Guild of Saint Luke in Bruges was a powerful medieval and early Renaissance artists’ and craftsmen’s guild that regulated the city’s painting and related visual arts professions.

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_69eeb31c925881909b597f6e40056d28 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61930bca08190a3eb5073627bacce completed May 2, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12132b4eb0819088608da95930f639 completed May 23, 2026, 8:50 p.m.
NEDg Description generation batch_6a1213f91bd48190a894a7bdca8c9447 completed May 23, 2026, 8:54 p.m.
NED2 Entity disambiguation (via description) batch_6a12150ca50881909438084adda62d39 completed May 23, 2026, 8:58 p.m.
Created at: April 27, 2026, 4:03 a.m.