Triple

T1590523
Position Surface form Disambiguated ID Type / Status
Subject Webex E34167 entity
Predicate hasComponent P35 FINISHED
Object Webex Calling E34167 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: Webex Calling | Statement: [Webex, hasComponent, Webex Calling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Webex Calling
Context triple: [Webex, hasComponent, Webex Calling]
  • A. Webex chosen
    Webex is Cisco’s cloud-based suite of video conferencing, online meeting, and team collaboration tools used by businesses and organizations worldwide.
  • B. NetMeeting
    NetMeeting was a Microsoft videoconferencing and collaboration application that enabled voice, video, and data sharing over the internet on Windows systems.
  • C. Google Meet
    Google Meet is a video conferencing service by Google that enables online meetings, voice calls, and screen sharing for individuals, businesses, and educational institutions.
  • D. Skype
    Skype is a widely used internet-based communication service that enables voice calls, video chats, and instant messaging across computers and mobile devices.
  • E. Skype for Business Online
    Skype for Business Online was Microsoft's cloud-based enterprise communication and collaboration service that provided messaging, meetings, and voice capabilities before being succeeded by Microsoft Teams.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621526e8819097d8c5330e527ed3 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad608ae5b4819080d769d6f6cbacda completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:27 p.m.