Triple

T5934392
Position Surface form Disambiguated ID Type / Status
Subject Eurofins Scientific E132007 entity
Predicate hasLaboratories P15417 FINISHED
Object over 900 laboratories worldwide LITERAL 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: over 900 laboratories worldwide | Statement: [Eurofins Scientific, hasLaboratories, over 900 laboratories worldwide]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLaboratories
Context triple: [Eurofins Scientific, hasLaboratories, over 900 laboratories worldwide]
  • A. laboratoryModule
    Indicates a relationship where an entity is a laboratory module or functions as a lab-specific component or unit within a larger system or structure.
  • B. hasResearchInfrastructure chosen
    Indicates that an entity possesses, controls, or provides access to facilities, equipment, or resources used to conduct research.
  • C. hasResearchCenters
    Indicates that an entity possesses, hosts, or is associated with one or more research centers.
  • D. hasResearchCentersIn
    Indicates that an entity maintains or operates research centers located within a specified place or region.
  • E. hasResearchHospital
    Indicates that an entity possesses, is associated with, or operates a hospital facility dedicated to conducting medical or clinical research.
  • F. None of above.

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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03f26f51881908cc253fe5775a1fc completed March 22, 2026, 7:12 p.m.
PD Predicate disambiguation batch_69c03355caf08190b960563a1aed23f9 completed March 22, 2026, 6:22 p.m.
Created at: March 22, 2026, 4 p.m.