Triple
T23828589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gypsy Queen (Santana arrangement) |
E589451
|
entity |
| Predicate | originalComposerNationality |
P143926
|
FINISHED |
| Object | Hungarian |
—
|
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: Hungarian | Statement: [Gypsy Queen (Santana arrangement), originalComposerNationality, Hungarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalComposerNationality Context triple: [Gypsy Queen (Santana arrangement), originalComposerNationality, Hungarian]
-
A.
associatedComposerNationality
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
B.
countryOfOriginOfComposer
chosen
Indicates the country from which a composer originates or is associated as their place of origin.
-
C.
primaryArtistNationality
Indicates the nationality associated with the main or primary artist involved in a work or context.
-
D.
originalPerformerNationality
Indicates the country or national identity associated with the performer who first performed the work or role.
-
E.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
- 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_69e25d1922d481909cab567c06a802ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f304f08190bd965df06f013b3f |
completed | April 29, 2026, 8:57 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8 p.m.