Triple
T20049038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhong |
E499141
|
entity |
| Predicate | tunedOrUntuned |
P138510
|
FINISHED |
| Object | tuned |
—
|
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: tuned | Statement: [Zhong, tunedOrUntuned, tuned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunedOrUntuned Context triple: [Zhong, tunedOrUntuned, tuned]
-
A.
isTunedTo
Indicates that one entity has been adjusted or configured to operate at, receive, or correspond to the frequency, channel, or setting of another entity.
-
B.
tunedBy
Indicates that one entity has been adjusted or calibrated in its settings, parameters, or configuration by another entity.
-
C.
tuningType
Indicates the specific method or configuration by which something is adjusted or calibrated to achieve a desired performance or behavior.
-
D.
tuningOfInstrument
Indicates the specific tuning configuration or pitch arrangement applied to a musical instrument.
-
E.
tuning
Indicates the adjustment or calibration of something’s parameters or settings to achieve desired performance or behavior.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:37 p.m.