Triple
T19895778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hammond organ |
E478147
|
entity |
| Predicate | hasKeyboardCount |
P137740
|
FINISHED |
| Object | two manuals in classic models |
—
|
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: two manuals in classic models | Statement: [Hammond organ, hasKeyboardCount, two manuals in classic models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyboardCount Context triple: [Hammond organ, hasKeyboardCount, two manuals in classic models]
-
A.
hasKeyboard
Indicates that one entity possesses or is equipped with a keyboard as a component or accessory.
-
B.
hasKeypadLayout
Indicates that one entity possesses or uses a specific arrangement or configuration of keys or buttons provided by another entity.
-
C.
hasPhysicalKeypad
Indicates that an entity is equipped with a tangible, button-based keypad for input or control.
-
D.
hasFunctionKeys
Indicates that an object or device possesses dedicated keys assigned to specific functions or shortcuts.
-
E.
supportsKeyboard
Indicates that one entity is compatible with or able to be operated using a keyboard as an input method.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6593cb45881909cc34a9c601db001 |
completed | April 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.