Triple
T23541712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurzweil K2000 |
E577768
|
entity |
| Predicate | hasTimbrality |
P152736
|
FINISHED |
| Object | 16-part multitimbral |
—
|
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: 16-part multitimbral | Statement: [Kurzweil K2000, hasTimbrality, 16-part multitimbral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimbrality Context triple: [Kurzweil K2000, hasTimbrality, 16-part multitimbral]
-
A.
hasTamga
Indicates that an entity bears or is marked with a specific tamga (a distinctive emblem, brand, or clan/ownership mark).
-
B.
hasBankCharacteristic
Indicates that a bank possesses a particular attribute, feature, or quality.
-
C.
hadImprint
Indicates that one entity bears or once bore a physical or symbolic mark, stamp, or impression produced by another entity.
-
D.
hasImprimatur
Indicates that an entity has received official approval or authorization, typically from a recognized authority.
-
E.
hasTarn
Indicates that something possesses or contains a tarn, i.e., a small mountain lake or pool.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1cb8b48190b51dd83b9fb116fe |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:10 p.m.