Triple
T34396587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyrie |
E882845
|
entity |
| Predicate | hasFamousSettingsBy |
P155903
|
FINISHED |
| Object | Johann Sebastian Bach |
—
|
NE NERFINISHED |
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: Johann Sebastian Bach | Statement: [Kyrie, hasFamousSettingsBy, Johann Sebastian Bach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFamousSettingsBy Context triple: [Kyrie, hasFamousSettingsBy, Johann Sebastian Bach]
-
A.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
B.
hasNotableSettingBy
Indicates that the subject has a notable or significant setting that was created, designed, or established by the specified entity.
-
C.
hasFamousPass
Indicates that an entity possesses or is associated with a well-known or historically significant pass (such as a route, corridor, or access point).
-
D.
hasSettingBy
chosen
Indicates that something (such as a work, event, or scenario) has its contextual environment, location, or background defined or established by a particular agent or source.
-
E.
hasFamousSignal
Indicates that an entity is associated with a well-known or widely recognized signal, message, or indicator.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:59 a.m.