Triple
T1050052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossmanith GmbH |
E22673
|
entity |
| Predicate | originated |
P1257
|
FINISHED |
| Object | TeamViewer software project |
—
|
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: TeamViewer software project | Statement: [Rossmanith GmbH, originated, TeamViewer software project]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originated Context triple: [Rossmanith GmbH, originated, TeamViewer software project]
-
A.
originallyIn
Indicates that something first appeared, was created, or was initially located within a particular context, source, or place.
-
B.
wasOriginally
Indicates that an entity had a particular state, form, type, or affiliation at an earlier time, which has since changed.
-
C.
emergedFrom
chosen
Indicates that one entity originated, arose, or came forth from another entity or source.
-
D.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
E.
cityOfOriginal
Indicates the city from which something or someone originally comes or was first created or established.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.