Triple

T1636321
Position Surface form Disambiguated ID Type / Status
Subject Red Hat Ansible Automation Platform E35365 entity
Predicate integratesWith P1075 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: [Red Hat Ansible Automation Platform, integratesWith, ServiceNow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ServiceNow
Context triple: [Red Hat Ansible Automation Platform, integratesWith, 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. 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.
  • E. Gainsight
    Gainsight is a customer success and product experience software company known for helping businesses reduce churn, drive expansion, and improve customer retention through data-driven insights and workflows.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a17e8e08190afb78a953ab920ec completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58dbd0608190be207ab2bcdc9eef completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.