Triple
T9445388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Symphony No. 5 in D major |
E227749
|
entity |
| Predicate | belongsToComposerNationalitySchool |
P12042
|
FINISHED |
| Object | English music |
—
|
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: English music | Statement: [Symphony No. 5 in D major, belongsToComposerNationalitySchool, English music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToComposerNationalitySchool Context triple: [Symphony No. 5 in D major, belongsToComposerNationalitySchool, English music]
-
A.
associatedComposerNationality
chosen
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
B.
worksWithArtistNationality
Indicates that one entity collaborates or is professionally associated in their work with artists of a specified nationality.
-
C.
associated artist nationality
Indicates the country or nationality with which an artist connected to the subject is identified.
-
D.
associatedWithSchool
Indicates a relationship where an entity has a connection or affiliation with a particular school, such as attendance, employment, or partnership.
-
E.
countryForAcademySubmission
Indicates the country that is officially submitting or representing an academy-related entry (such as a film or work) for consideration.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f33deb88190bc74968575963ac4 |
completed | April 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.