Triple
T22065580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Girls Learn Love Hard |
E545257
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Ras Baraka |
—
|
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: Ras Baraka | Statement: [Black Girls Learn Love Hard, creator, Ras Baraka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ras Baraka Context triple: [Black Girls Learn Love Hard, creator, Ras Baraka]
-
A.
Ras Baraka
chosen
Ras Baraka is an American politician, educator, and poet who serves as the progressive mayor of Newark, New Jersey.
-
B.
Ras Kass
Ras Kass is an American rapper from California known for his complex lyricism, dense wordplay, and socially conscious, often politically charged content.
-
C.
Ras Dashen
Ras Dashen is a prominent mountain peak in northern Ethiopia, renowned as the country’s highest summit and a key feature of the Simien Mountains.
-
D.
Ramlala Nahachhu
Ramlala Nahachhu is a lesser-known devotional work attributed to the 16th-century Hindu poet-saint Tulsidas, celebrated for his writings on Lord Rama.
-
E.
Negus
Negus was a royal title used in Ethiopia for kings or rulers, ranking below the emperor.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12883d2108190a6127783f8f635fc |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:27 p.m.