Triple
T2867657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Schweitzer |
E63477
|
entity |
| Predicate | musicalSpecialty |
P26585
|
FINISHED |
| Object | organ performance |
—
|
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: organ performance | Statement: [Albert Schweitzer, musicalSpecialty, organ performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicalSpecialty Context triple: [Albert Schweitzer, musicalSpecialty, organ performance]
-
A.
genreSpecialty
Indicates that an entity specializes in or is particularly associated with a specific genre.
-
B.
musicalAbility
chosen
Indicates that an entity possesses skill, talent, or proficiency in performing, creating, or understanding music.
-
C.
styleOfMusic
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
D.
musicInstrumentation
Indicates the specific instruments or instrumental forces used to perform a piece of music.
-
E.
partOfMusical
Indicates that something is a component, segment, or element belonging to a larger musical work or performance.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfbcebcc81909a78a1787d823e3e |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.