Triple

T3451912
Position Surface form Disambiguated ID Type / Status
Subject Gainsight E72810 entity
Predicate integratesWith P1075 FINISHED
Object HubSpot E292741 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: HubSpot | Statement: [Gainsight, integratesWith, HubSpot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HubSpot
Context triple: [Gainsight, integratesWith, HubSpot]
  • A. HubSpot chosen
    HubSpot is a leading customer relationship management (CRM) and marketing automation platform that helps businesses attract, engage, and retain customers.
  • B. Marketo
    Marketo is a leading marketing automation software platform that helps businesses manage and optimize digital marketing campaigns and customer engagement.
  • C. Base CRM
    Base CRM was a sales-focused customer relationship management platform known for its intuitive interface and mobile-first design, later integrated into Zendesk’s product suite after acquisition.
  • D. Sprinklr
    Sprinklr is a customer experience management and social media analytics software company that helps large enterprises manage and optimize interactions across digital channels.
  • E. Zoho Connect
    Zoho Connect is a team collaboration and communication platform by Zoho that offers features like group discussions, file sharing, and task management to streamline workplace collaboration.
  • 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_69ad85b12a908190a1d10a6b03b4f8ae completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba7465248190947f9096e230e1c4 completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360ef69308190a11f37ddbf3bbc7b completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:16 p.m.