Triple

T12389846
Position Surface form Disambiguated ID Type / Status
Subject Microsoft Viva Learning E295960 entity
Predicate accessMethod P5872 FINISHED
Object Teams app E5699 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: Teams app | Statement: [Microsoft Viva Learning, accessMethod, Teams app]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teams app
Context triple: [Microsoft Viva Learning, accessMethod, Teams app]
  • A. Teams chosen
    Teams is Microsoft's cloud-based collaboration and communication platform that integrates chat, video meetings, file sharing, and app integrations for organizations.
  • B. TD app
    TD app is a mobile trading and account management application offered by TD Direct Investing for buying, selling, and monitoring investments.
  • C. TeamSystem
    TeamSystem is an Italian software company specializing in business management and accounting solutions for small and medium-sized enterprises.
  • D. Zoho Cliq
    Zoho Cliq is a team communication and collaboration platform offering real-time messaging, channels, and integrations for workplace productivity.
  • E. Yammer
    Yammer is an enterprise social networking service that enables employees within an organization to communicate, collaborate, and share information in a secure, Facebook-like environment.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fcf6aa8819080c9a2407a72db2e completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63479df38819085c5ca791c460d5e completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:54 p.m.