Triple

T3351028
Position Surface form Disambiguated ID Type / Status
Subject Dilan Yeşilgöz-Zegerius E70491 entity
Predicate countryOfPoliticalActivity P14332 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: [Dilan Yeşilgöz-Zegerius, countryOfPoliticalActivity, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netherlands
Context triple: [Dilan Yeşilgöz-Zegerius, countryOfPoliticalActivity, 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 historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • C. 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.
  • D. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb220721c81909eb4d8d35c923927 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b35456814c8190a8e4d53935af539a completed March 13, 2026, 12:03 a.m.
Created at: March 8, 2026, 3:12 p.m.