Triple

T4831984
Position Surface form Disambiguated ID Type / Status
Subject O'Reilly Online Learning platform E107965 entity
Predicate supportsOrganizationUseCase P60279 FINISHED
Object employee upskilling 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: employee upskilling | Statement: [O'Reilly Online Learning platform, supportsOrganizationUseCase, employee upskilling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: supportsOrganizationUseCase
Context triple: [O'Reilly Online Learning platform, supportsOrganizationUseCase, employee upskilling]
  • A. supportsOrganization
    Indicates that one entity provides assistance, resources, or advocacy that helps sustain or advance an organization.
  • B. supportsUse
    Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
  • C. usedInOrganization
    Indicates that something (such as a tool, method, or resource) is employed or applied within a particular organization.
  • D. usedByOrganizationType
    Indicates that something is utilized or employed by organizations of a specified type.
  • E. usesCoverOrganizations
    Indicates that an entity operates through or makes use of front or intermediary organizations to conceal its true identity, role, or activities.
  • F. None of above. chosen

Provenance (4 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ff981fc819080d4466c6fe06cf3 completed March 20, 2026, 4:04 p.m.
PD Predicate disambiguation batch_69bd6c21c7f08190846049d31fdfa144 completed March 20, 2026, 3:47 p.m.
PDg Predicate description generation batch_69bd6ff731188190a9903602122d4ff9 completed March 20, 2026, 4:04 p.m.
Created at: March 20, 2026, 1:24 p.m.