Triple

T3810898
Position Surface form Disambiguated ID Type / Status
Subject Gerard ter Borch E93129 entity
Predicate workLocation P7 FINISHED
Object Deventer E360206 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: Deventer | Statement: [Gerard ter Borch, workLocation, Deventer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deventer
Context triple: [Gerard ter Borch, workLocation, Deventer]
  • A. Deventer chosen
    Deventer is a historic Dutch city known for its medieval architecture, Hanseatic trading past, and annual book market.
  • B. Venlo
    Venlo is a historic city in the southeastern Netherlands, located near the German border on the river Meuse and known as a regional economic and logistics hub.
  • C. Hoorn
    Hoorn is a historic port city in the Netherlands known for its role in the Dutch Golden Age and as a former base of the Dutch East India Company.
  • D. Culemborg
    Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
  • E. Zutphen
    Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80faaa88190b05f8aec8aa5c44d completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65f9d763c81908bdc6d9cfc718a55 completed March 27, 2026, 10:44 a.m.
Created at: March 9, 2026, 3:16 p.m.