Triple
T8900723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantasia on Greensleeves |
E211921
|
entity |
| Predicate | associatedNationalityOfComposer |
P12042
|
FINISHED |
| Object | English |
—
|
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 | Statement: [Fantasia on Greensleeves, associatedNationalityOfComposer, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedNationalityOfComposer Context triple: [Fantasia on Greensleeves, associatedNationalityOfComposer, English]
-
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.
associated artist nationality
Indicates the country or nationality with which an artist connected to the subject is identified.
-
C.
hasMusicalComposer
Indicates that one entity serves as the musical composer responsible for creating the music associated with another entity.
-
D.
primaryArtistNationality
Indicates the nationality associated with the main or primary artist involved in a work or context.
-
E.
performingArtistNationality
Indicates the nationality or country of origin of the artist who performs a given 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6428ffc48190814f6b865961dbd1 |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2bfb38819083d5eb1af8ccf4d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:54 p.m.