Triple

T706410
Position Surface form Disambiguated ID Type / Status
Subject Leiden E14108 entity
Predicate locatedIn 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: [Leiden, locatedIn, Randstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randstad
Context triple: [Leiden, locatedIn, 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. 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.
  • D. Towers Watson
    Towers Watson was a global professional services firm specializing in risk management, insurance brokerage, and human capital consulting.
  • E. Rockwell Group
    Rockwell Group is a renowned New York–based architecture and design firm known for its innovative, experience-driven projects across hospitality, entertainment, and cultural spaces worldwide.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a54607f08190b3ee4805f2ea4b2f completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66d9140148190a439ac7a03ee88b2 completed March 3, 2026, 5:11 a.m.
Created at: March 1, 2026, 7:36 p.m.