Triple

T4679252
Position Surface form Disambiguated ID Type / Status
Subject Old Rhine E103757 entity
Predicate region P40 FINISHED
Object Randstad E33858 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: Randstad | Statement: [Old Rhine, region, Randstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randstad
Context triple: [Old Rhine, region, Randstad]
  • A. ManpowerGroup
    ManpowerGroup is a global workforce solutions and staffing services company that provides recruitment, talent management, and outsourcing services to businesses worldwide.
  • B. Randstad metropolitan region chosen
    The Randstad metropolitan region is a densely populated urban area in the western Netherlands that includes major cities such as Amsterdam, Rotterdam, The Hague, and Utrecht, forming the country’s primary economic and cultural hub.
  • C. Recruit Holdings
    Recruit Holdings is a Japanese human resources and marketing conglomerate best known globally as the owner of major job search platform Indeed.
  • D. Groupe ADP
    Groupe ADP is a major French airport management company that owns and operates the Paris-area airports and provides aviation and related services worldwide.
  • E. Towers Watson
    Towers Watson was a global professional services firm specializing in risk management, insurance brokerage, and human capital consulting.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd636acffc819094e03c5bb53203d8 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03a497ac8190bd278a4bd531aa45 completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:16 p.m.