Triple

T16420440
Position Surface form Disambiguated ID Type / Status
Subject Everhard E398801 entity
Predicate hasUsage P2529 FINISHED
Object Netherlands E864 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: Netherlands | Statement: [Everhard, hasUsage, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netherlands
Context triple: [Everhard, hasUsage, Netherlands]
  • A. Netherlands chosen
    The Netherlands is a Western European country known for its low-lying geography, extensive canal systems, and historically significant role in global trade and European politics.
  • B. Nederland
    Nederland is a small mountain town in Colorado known for its scenic setting near the Rocky Mountains and its quirky local culture.
  • C. Holland
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • D. Holland
    Holland is a regional less-than-truckload (LTL) freight carrier in the United States known for its operations in the Midwest and surrounding areas.
  • E. Holland
    Holland is a small settlement on the Orkney island of Stronsay in Scotland, known for its rural character and coastal surroundings.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f5c1bc8190a679f35bd6c0bc97 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f3d8f188190969b75d82c6b13f0 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:09 a.m.