Triple

T816807
Position Surface form Disambiguated ID Type / Status
Subject Salesforce E17666 entity
Predicate acquired P2511 FINISHED
Object MuleSoft E97094 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: MuleSoft | Statement: [Salesforce, acquired, MuleSoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MuleSoft
Context triple: [Salesforce, acquired, MuleSoft]
  • A. MuleSoft chosen
    MuleSoft is an integration and API management platform that helps organizations connect applications, data, and devices across cloud and on-premises environments.
  • 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. 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.
  • D. Palantir Technologies
    Palantir Technologies is an American software company specializing in big data analytics platforms used by governments and large enterprises for intelligence, security, and operational decision-making.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7928f8a808190aaf5f2a2f3ee676f completed March 4, 2026, 2:01 a.m.
Created at: March 1, 2026, 7:38 p.m.