Triple

T11420627
Position Surface form Disambiguated ID Type / Status
Subject ManpowerGroup E270607 entity
Predicate brand P1500 FINISHED
Object Experis E55020 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: Experis | Statement: [ManpowerGroup, brand, Experis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Experis
Context triple: [ManpowerGroup, brand, Experis]
  • A. Cognizant
    Cognizant is a multinational information technology services and consulting company known for providing digital, technology, consulting, and operations services to clients worldwide.
  • B. ManpowerGroup chosen
    ManpowerGroup is a global workforce solutions and staffing services company that provides recruitment, talent management, and outsourcing services to businesses worldwide.
  • C. Accenture
    Accenture is a global professional services company specializing in consulting, technology, and outsourcing solutions for businesses and governments worldwide.
  • D. Capgemini
    Capgemini is a global consulting, technology services, and digital transformation company headquartered in France.
  • E. HCL Technologies
    HCL Technologies is a global Indian IT services and consulting company known for providing software development, infrastructure management, and digital transformation solutions to enterprises 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d801b20ce08190befc98379b879985 completed April 9, 2026, 7:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b88f80d88190b91b63d0b7457c25 completed April 20, 2026, 5:24 a.m.
Created at: April 8, 2026, 9:34 p.m.