Triple
T12259395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Lo |
E292181
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | Sugarcane |
E292185
|
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: Sugarcane | Statement: [Ma Lo, album, Sugarcane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sugarcane Context triple: [Ma Lo, album, Sugarcane]
-
A.
Sugarcane
chosen
Sugarcane is a 2017 EP by Nigerian singer Tiwa Savage that blends Afrobeats, R&B, and pop influences and helped solidify her status as a leading figure in contemporary African music.
-
B.
Bagassa
Bagassa is a small genus of tropical trees in the mulberry family, known for species such as Bagassa guianensis found in South American rainforests.
-
C.
Tebu
Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
-
D.
Bambou
Bambou is a French singer, actress, and model best known as the longtime companion and muse of musician Serge Gainsbourg in the 1980s.
-
E.
Maní
Maní is a rural municipality in Colombia’s Casanare Department, known for its cattle ranching, oil-related activities, and Llanos (plains) landscapes.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cd964ec81908241d2b9a96d1025 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60ac1b5148190838b782848e3fa36 |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:52 p.m.