Triple

T14454081
Position Surface form Disambiguated ID Type / Status
Subject Nick Mehta E358408 entity
Predicate employer P7 FINISHED
Object Gainsight E72810 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: Gainsight | Statement: [Nick Mehta, employer, Gainsight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gainsight
Context triple: [Nick Mehta, employer, Gainsight]
  • A. Gainsight chosen
    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.
  • B. 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.
  • C. Appirio
    Appirio is a cloud services and consulting company known for helping enterprises implement and optimize platforms like Salesforce and Workday.
  • D. Arvato CRM Solutions
    Arvato CRM Solutions is a business process outsourcing provider specializing in customer relationship management services such as customer care, technical support, and digital communication for corporate clients.
  • E. Ultimate Software
    Ultimate Software was a leading American provider of cloud-based human capital management and payroll software solutions for businesses.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91a8bf088190abf5fd4f646b8c62 completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8aa904c08190b33796b832aa100f completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:19 a.m.