Triple

T13684250
Position Surface form Disambiguated ID Type / Status
Subject Bunschoten E328079 entity
Predicate region P40 FINISHED
Object Eemland E913566 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: Eemland | Statement: [Bunschoten, region, Eemland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eemland
Context triple: [Bunschoten, region, Eemland]
  • A. Eemland region chosen
    The Eemland region is an area in the central Netherlands, around the city of Amersfoort, known for its low-lying polder landscapes and proximity to the Eem River.
  • B. Maasland
    Maasland is a historical region in the Low Countries centered along the river Meuse, known for its medieval political and cultural significance.
  • C. Hollandia
    Hollandia is an engineering firm known for its role in designing and constructing major structures such as the London Eye.
  • D. Hollandia
    Hollandia was a major World War II Allied military base and logistical hub in New Guinea, used as a key staging area for operations in the South West Pacific.
  • E. Zoutelande
    Zoutelande is a coastal village and popular seaside resort in the Dutch province of Zeeland, known for its beaches and dunes along the North Sea.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66f8acc8190b2a82b722930b995 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944765488190a97d2bea8c29e698 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.