Triple
T21674350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tele |
E534928
|
entity |
| Predicate | hasTuningMachines |
P65514
|
FINISHED |
| Object | 6 inline tuning machines |
—
|
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: 6 inline tuning machines | Statement: [Tele, hasTuningMachines, 6 inline tuning machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTuningMachines Context triple: [Tele, hasTuningMachines, 6 inline tuning machines]
-
A.
tuningMachines
chosen
Indicates a relationship where an instrument or device is equipped with or associated with specific tuning machines used to adjust string tension.
-
B.
hasFrets
Indicates that an instrument or similar object possesses frets, i.e., raised elements on its neck or surface that divide it into fixed pitch intervals.
-
C.
tuningOfInstrument
Indicates the specific tuning configuration or pitch arrangement applied to a musical instrument.
-
D.
tunedOrUntuned
Indicates whether something is in a properly adjusted or calibrated state (tuned) or not (untuned).
-
E.
hadInstrument
Indicates that an action or event was performed using a particular instrument or tool.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a0ed5388190b8f1932fb3f11c6a |
completed | April 27, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:41 p.m.