Triple

T2955162
Position Surface form Disambiguated ID Type / Status
Subject YRC Worldwide E79914 entity
Predicate hasSubsidiary P254 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: [YRC Worldwide, hasSubsidiary, Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holland
Context triple: [YRC Worldwide, hasSubsidiary, Holland]
  • A. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • B. Holland chosen
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • C. 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.
  • D. 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.
  • E. Friesland
    Friesland is a northern province of the Netherlands known for its distinct Frisian language, rich maritime history, and unique cultural traditions.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99286ac8819084f02fbb0a1616d3 completed March 8, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eedb51b88190b7a009d45361fd32 completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 2:57 p.m.