Triple

T3645749
Position Surface form Disambiguated ID Type / Status
Subject Nishi Amane E77295 entity
Predicate studiedIn P770 FINISHED
Object the 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: the Netherlands | Statement: [Nishi Amane, studiedIn, the Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: the Netherlands
Context triple: [Nishi Amane, studiedIn, the 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. 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.
  • C. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • D. Holland
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • E. Belgium
    Belgium is a Western European country known for its role as a founding member of major international organizations, including NATO and the European Union, and for hosting many of their key institutions.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc35da84c81908950de92ba171fa3 completed March 8, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f01ef3e08190bb5ebfde40787ff2 completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:24 p.m.