Triple
T38469580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Omar: The Ultimate Collection Vol. 9 |
E912672
|
entity |
| Predicate | hasPrimaryArtistFullName |
P7867
|
FINISHED |
| Object | William Omar Landrón Rivera |
E909730
|
NE 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: William Omar Landrón Rivera | Statement: [Don Omar: The Ultimate Collection Vol. 9, hasPrimaryArtistFullName, William Omar Landrón Rivera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryArtistFullName Context triple: [Don Omar: The Ultimate Collection Vol. 9, hasPrimaryArtistFullName, William Omar Landrón Rivera]
-
A.
primaryArtist
chosen
Indicates that an entity is the main or lead artist responsible for a creative work, as opposed to supporting or contributing artists.
-
B.
parentAlbumArtistFullName
Indicates the full name of the artist associated with the parent album of the given entity.
-
C.
hasPerformerGivenName
Indicates that a performer is associated with a specific given (first) name.
-
D.
performerFullName
Indicates the complete name of the entity that performs an action or role in the described context.
-
E.
hasArtistLegalName
Indicates that an artist entity is associated with a specific legal (real) name used for official or formal purposes.
- F. None of above.
Provenance (4 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a5ae31738588190aba2168cb762a961 |
completed | July 18, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.