Triple

T3430133
Position Surface form Disambiguated ID Type / Status
Subject Genesys E72316 entity
Predicate product P490 FINISHED
Object Genesys Engage E72316 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: Genesys Engage | Statement: [Genesys, product, Genesys Engage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genesys Engage
Context triple: [Genesys, product, Genesys Engage]
  • A. Genesys chosen
    Genesys is a global customer experience and contact center technology company known for its cloud-based solutions that help businesses manage and optimize customer interactions.
  • B. Amazon Connect
    Amazon Connect is a cloud-based contact center service that enables businesses to set up and manage scalable customer support and call center operations using Amazon Web Services infrastructure.
  • C. Twilio
    Twilio is a cloud communications platform company that enables developers and businesses to integrate voice, messaging, video, and authentication capabilities into their applications via APIs.
  • D. Opsware
    Opsware was a data center automation and IT infrastructure management software company, best known for being co-founded by Marc Andreessen and later acquired by Hewlett-Packard.
  • E. Avaya
    Avaya is an American multinational technology company specializing in business communications, unified communications, and contact center solutions for enterprises and organizations worldwide.
  • 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_69ad85ae14308190bcbc25cfa0246c0b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9bd61908190a7bdd01f24334fc3 completed March 8, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360c789b48190807bddf1a3bf8d2e completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:15 p.m.