Triple

T16869161
Position Surface form Disambiguated ID Type / Status
Subject Paris–Amsterdam high-speed corridor E410123 entity
Predicate countryServed P1083 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: [Paris–Amsterdam high-speed corridor, countryServed, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netherlands
Context triple: [Paris–Amsterdam high-speed corridor, countryServed, 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b50a82348190b3e33fd558aa3c7f completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45013048190a8073f34820ca85a completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:24 a.m.