Triple

T19209299
Position Surface form Disambiguated ID Type / Status
Subject Automatic Data Processing E480315 entity
Predicate shortName P43 FINISHED
Object ADP NE NERFINISHED

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: ADP | Statement: [Automatic Data Processing, shortName, ADP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ADP
Context triple: [Automatic Data Processing, shortName, ADP]
  • A. ADP chosen
    ADP is a leading global provider of payroll, human capital management, and HR outsourcing solutions for businesses of all sizes.
  • B. 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.
  • C. Workday
    Workday is a cloud-based enterprise software company best known for its human capital management and financial management applications used by large organizations worldwide.
  • D. ASDP
    ASDP is the professional abbreviation for the American Society of Dermatopathology, an organization dedicated to the study and advancement of skin pathology.
  • E. ADK
    ADK is the National Rail station code for Ardwick railway station in Manchester, England.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8cb8c348190b52075823911c869 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5f9a000188190afb762ea24bc3deb completed April 20, 2026, 10:02 a.m.
Created at: April 10, 2026, 1:20 p.m.