Triple
T3426193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google Play Music |
E72234
|
entity |
| Predicate | platform |
P1292
|
FINISHED |
| Object | Sonos |
E112747
|
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: Sonos | Statement: [Google Play Music, platform, Sonos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonos Context triple: [Google Play Music, platform, Sonos]
-
A.
Sonos
chosen
Sonos is a company best known for its wireless multi-room home audio systems and smart speakers that integrate with numerous music streaming services.
-
B.
Nest Audio
Nest Audio is a smart speaker by Google that offers high-quality sound and voice-controlled access to Google services and smart home features.
-
C.
B&O Warehouse
B&O Warehouse is a historic former railroad warehouse in Baltimore that forms the iconic brick backdrop beyond the right-field wall at Oriole Park at Camden Yards.
-
D.
Bose
Bose is a common Indian surname most prominently associated with physicist Satyendra Nath Bose, whose work led to the concept of bosons and Bose–Einstein statistics.
-
E.
Denon Wing
Denon Wing is one of the main wings of the Louvre Museum in Paris, housing many of its most famous artworks, including Leonardo da Vinci’s Mona Lisa.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9812a648190ac919e7291744b5a |
completed | March 8, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b354766bcc81909fb3124262c93f8f |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:15 p.m.