Triple
T30384022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony MDR-V6 |
E772899
|
entity |
| Predicate | hasLabeling |
P77334
|
FINISHED |
| Object | red "V6" badge on earcup |
—
|
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: red "V6" badge on earcup | Statement: [Sony MDR-V6, hasLabeling, red "V6" badge on earcup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLabeling Context triple: [Sony MDR-V6, hasLabeling, red "V6" badge on earcup]
-
A.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
B.
labelingType
Indicates the specific kind or category of labeling applied to an entity or between entities, such as the method, standard, or purpose of the label.
-
C.
usedInLabeling
Indicates that something is employed or applied as part of a labeling process or activity.
-
D.
hasLabelSet
Indicates that an entity is associated with a specific collection or set of labels.
-
E.
isLabeledOn
chosen
Indicates that a label, tag, or identifying text is physically or virtually attached to or displayed on an entity.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: April 29, 2026, 8:01 p.m.