Triple
T14819598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariel |
E348409
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Omo |
E987462
|
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: Omo | Statement: [Ariel, competitor, Omo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omo Context triple: [Ariel, competitor, Omo]
-
A.
Omo
Omo is a track from Burna Boy’s acclaimed album "African Giant," showcasing his fusion of Afro-fusion rhythms and socially conscious lyrics.
-
B.
Omo
chosen
Omo is a widely recognized global laundry detergent brand known for its stain-removal performance and household cleaning products.
-
C.
Omoba
Omoba is a popular Afro-pop single by Nigerian artist D'Prince, known for its catchy hooks and club-friendly production.
-
D.
Omolu
Omolu is an orixá in Afro-Brazilian religion, particularly revered as a powerful deity of disease, healing, and the dead.
-
E.
Omo-Tana
Omo-Tana is a subbranch of the Cushitic language family comprising several closely related languages spoken primarily in parts of Ethiopia, Kenya, and Somalia.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe4cf38819090f25ef045351d5d |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe389940e081908ad627955cb8d52e |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 10, 2026, 1:50 a.m.