Triple
T10852369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivaldi web browser |
E256179
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Vivaldi Technologies |
E257450
|
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: Vivaldi Technologies | Statement: [Vivaldi web browser, developer, Vivaldi Technologies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vivaldi Technologies Context triple: [Vivaldi web browser, developer, Vivaldi Technologies]
-
A.
Vivaldi Technologies
chosen
Vivaldi Technologies is a software company best known for developing the highly customizable Vivaldi web browser, founded by former Opera CEO Jon Stephenson von Tetzchner.
-
B.
Vivaldi web browser
Vivaldi web browser is a highly customizable, privacy-focused web browser built on Chromium, known for its advanced user interface controls and productivity features.
-
C.
Opera Software
Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
-
D.
Amoeba Technologies
Amoeba Technologies is a technology company whose board has included noted innovation and organizational learning expert John Seely Brown.
-
E.
Azul Systems
Azul Systems is a software company specializing in high-performance, scalable Java runtimes and JVM technologies for enterprise applications.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75117b76c8190b0fb216b1428c3c7 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb17d978c8190883b4a56e88859de |
completed | April 14, 2026, 9:28 p.m. |
Created at: April 8, 2026, 9:20 p.m.