Triple

T5033557
Position Surface form Disambiguated ID Type / Status
Subject Elisabeth Vermeer E113364 entity
Predicate region P40 FINISHED
Object Holland E308544 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: Holland | Statement: [Elisabeth Vermeer, region, Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holland
Context triple: [Elisabeth Vermeer, region, Holland]
  • A. Holland chosen
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • 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. Netherlands
    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.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b68d8c8190b8e04fb406abdb0f completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfb4215c819086d0f4b412de9f2d completed March 21, 2026, 5:04 p.m.
Created at: March 20, 2026, 1:36 p.m.