Triple

T2402142
Position Surface form Disambiguated ID Type / Status
Subject John Donahoe E47791 entity
Predicate boardMemberOf P10 FINISHED
Object ServiceNow E59295 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: ServiceNow | Statement: [John Donahoe, boardMemberOf, ServiceNow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ServiceNow
Context triple: [John Donahoe, boardMemberOf, ServiceNow]
  • A. ServiceNow chosen
    ServiceNow is a cloud-based software company best known for its enterprise workflow and IT service management platform that helps organizations automate and streamline business processes.
  • B. Zendesk
    Zendesk is a customer service and engagement software company best known for its cloud-based help desk and support ticketing solutions used by businesses worldwide.
  • C. Appirio
    Appirio is a cloud services and consulting company known for helping enterprises implement and optimize platforms like Salesforce and Workday.
  • D. Jira
    Jira is a widely used project and issue tracking platform, especially popular among software development teams for managing tasks, bugs, and agile workflows.
  • E. Salesforce
    Salesforce is a leading cloud-based customer relationship management (CRM) company known for its suite of enterprise applications for sales, service, marketing, and analytics.
  • 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8f623908190875fdbc95c944f33 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf3d44b48190aa405ee612cdf57c completed March 9, 2026, 12:38 p.m.
Created at: March 4, 2026, 7:57 p.m.