Triple
T23940675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | guzheng |
E602772
|
entity |
| Predicate | usesAccessory |
P31021
|
FINISHED |
| Object | finger picks |
—
|
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: finger picks | Statement: [guzheng, usesAccessory, finger picks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAccessory Context triple: [guzheng, usesAccessory, finger picks]
-
A.
accessory
chosen
Indicates that one entity serves as a supplementary or supporting item to another, often enhancing its function, use, or appearance.
-
B.
hasAccessoryType
Indicates that an entity is associated with or characterized by a particular type or category of accessory.
-
C.
usesEquipment
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
D.
hasAccessoryEcosystem
Indicates that an entity is associated with a surrounding set of compatible accessories, add-ons, or peripheral products designed to work with it.
-
E.
usesProduct
Indicates that one entity makes use of, applies, or employs a particular product.
- 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_69e2953cf6e081909b8e25a10a52dddc |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d02a1b308190a2d101774b455417 |
completed | April 29, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:09 p.m.