Triple
T8428645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TQG |
E199063
|
entity |
| Predicate | albumArtist |
P1952
|
FINISHED |
| Object | Karol G |
E208768
|
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: Karol G | Statement: [TQG, albumArtist, Karol G]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karol G Context triple: [TQG, albumArtist, Karol G]
-
A.
Karol G
chosen
Karol G is a Colombian reggaeton and Latin trap singer-songwriter known for her chart-topping hits and major influence in contemporary Latin urban music.
-
B.
Rosalía
Rosalía is a Spanish singer and songwriter known for blending flamenco with contemporary pop and urban music, gaining international acclaim for her innovative sound and visuals.
-
C.
Gaby Moreno
Gaby Moreno is a Guatemalan singer-songwriter and guitarist known for her soulful blend of Latin, blues, jazz, and folk music.
-
D.
Kany García
Kany García is a Puerto Rican singer-songwriter known for her emotive Latin pop and ballads, multiple Latin Grammy Awards, and advocacy for LGBTQ+ rights.
-
E.
Anitta
Anitta is a Brazilian singer, songwriter, and performer known for her influential role in Latin pop and funk carioca and for high-profile international collaborations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd125a53c8190b83a4f6148baa779 |
completed | March 31, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf27e1bda481909062b9259a168eb0 |
completed | April 3, 2026, 2:37 a.m. |
Created at: March 30, 2026, 6:07 p.m.