Triple
T181098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TeamViewer |
E3877
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | TeamViewer Meeting |
E3877
|
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: TeamViewer Meeting | Statement: [TeamViewer, product, TeamViewer Meeting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TeamViewer Meeting Context triple: [TeamViewer, product, TeamViewer Meeting]
-
A.
TeamViewer
chosen
TeamViewer is a German software company best known for its remote access and remote control solutions that allow users to connect to and manage devices over the internet.
-
B.
Zoom Video Communications
Zoom Video Communications is a technology company best known for its widely used cloud-based video conferencing and online collaboration platform.
-
C.
Skype
Skype is a widely used internet-based communication service that enables voice calls, video chats, and instant messaging across computers and mobile devices.
-
D.
WebRTC
WebRTC is an open web technology that enables real-time audio, video, and data communication directly between browsers and devices without requiring plugins.
-
E.
ChatGPT Enterprise
ChatGPT Enterprise is OpenAI’s business-grade version of ChatGPT, offering enhanced security, admin controls, and scalable access to advanced AI capabilities for organizations.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25923507c8190bd7f6eda404b0da0 |
completed | Feb. 28, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2f0b71080819086362f6036b41162 |
completed | Feb. 28, 2026, 1:42 p.m. |
Created at: Feb. 28, 2026, 2:40 a.m.