Triple
T181124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TeamViewer |
E3877
|
entity |
| Predicate | targetUser |
P481
|
FINISHED |
| Object | business users |
—
|
LITERAL 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: business users | Statement: [TeamViewer, targetUser, business users]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetUser Context triple: [TeamViewer, targetUser, business users]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
targetMarket
chosen
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
C.
primaryUser
Indicates that the referenced user is the main or principal user associated with a given account, resource, or context.
-
D.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
E.
notableUser
Indicates that the user holds a special or distinguished status, such as being recognized, influential, or otherwise noteworthy within a given context.
- F. None of above.
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. |
| PD | Predicate disambiguation | batch_69a2566ccc288190add5624ede96d82b |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.