Triple
T30350716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony WI-C310 |
E771980
|
entity |
| Predicate | hasTrackControl |
P196866
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sony WI-C310, hasTrackControl, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrackControl Context triple: [Sony WI-C310, hasTrackControl, yes]
-
A.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
B.
hasTrackContext
Indicates that an entity is associated with or occurs within a particular track-related context (such as a specific track, route, or sequence).
-
C.
hasTrackSurface
Indicates that an entity (such as a track) possesses or is characterized by a particular type of surface.
-
D.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
-
E.
hasTrackSelection
Indicates that an entity is associated with a specific choice or configuration among multiple available tracks (such as audio, video, or data streams).
- F. None of above. chosen
Provenance (4 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe6c811bcc81908b1e1b1f8bcb071b |
completed | May 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69fe6c026d5481908b7a814dcf38c183 |
completed | May 8, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fe6c7fc4388190aa88993d00872d7f |
completed | May 8, 2026, 11:06 p.m. |
Created at: April 29, 2026, 7:56 p.m.