Triple
T22039887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbie: The Album |
E544309
|
entity |
| Predicate | includesTrack |
P3284
|
FINISHED |
| Object | Watati |
—
|
NE NERFINISHED |
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: Watati | Statement: [Barbie: The Album, includesTrack, Watati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Watati Context triple: [Barbie: The Album, includesTrack, Watati]
-
A.
Watati
chosen
"Watati" is a reggaeton-influenced song by Colombian singer Karol G, featured on the soundtrack of the 2023 film "Barbie."
-
B.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
-
C.
Kinyara
Kinyara is a town in Uganda’s Masindi District, best known for its large sugar estate and associated agro-industrial activities.
-
D.
Mahisha
Mahisha is a powerful buffalo demon in Hindu mythology, best known as the adversary slain by the goddess Durga in a pivotal cosmic battle between good and evil.
-
E.
Mabika
Mabika is the surname of Mwadi Mabika, a notable Congolese basketball player who competed internationally and in the WNBA.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f532b08190be80c5af039b4c29 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:25 p.m.