Triple
T28962521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Última (piano version) |
E731943
|
entity |
| Predicate | hasOriginalSongLanguage |
P95610
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Última (piano version), hasOriginalSongLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalSongLanguage Context triple: [Última (piano version), hasOriginalSongLanguage, Spanish]
-
A.
originalLanguageOfSourceSong
chosen
Indicates that a given language is the original language in which a particular source song was created or first written.
-
B.
containsOriginalSongs
Indicates that one entity includes or features songs that are original compositions rather than covers or adaptations.
-
C.
hasOriginalMusicBy
Indicates that the original musical score or soundtrack for a work was created or composed by a specified entity.
-
D.
originalLanguageOfMelody
Indicates that a specified language is the language in which a particular melody was originally created or first composed.
-
E.
hasOriginalLyricist
Indicates that an entity (such as a musical or song) is associated with the person who first wrote its lyrics.
- 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 28, 2026, 8:50 a.m.