Triple
T8507663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G Herbo |
E201373
|
entity |
| Predicate | stageName |
P7872
|
FINISHED |
| Object | G Herbo |
E201373
|
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: G Herbo | Statement: [G Herbo, stageName, G Herbo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: G Herbo Context triple: [G Herbo, stageName, G Herbo]
-
A.
G Herbo
chosen
G Herbo is an American rapper from Chicago known for his gritty drill-influenced style and vivid storytelling about street life.
-
B.
Tee Grizzley
Tee Grizzley is an American rapper from Detroit known for his gritty storytelling and breakout hit "First Day Out."
-
C.
Sheck Wes
Sheck Wes is an American rapper and songwriter best known for his breakout hit single "Mo Bamba" and his association with Kanye West’s GOOD Music label.
-
D.
Smino
Smino is an American rapper and singer known for his melodic, genre-blending style and inventive wordplay within contemporary hip-hop and R&B.
-
E.
French Montana
French Montana is a Moroccan-American rapper and songwriter known for hits like "Unforgettable" and his prominent role in the New York hip-hop scene.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5de18448190a695eec609b34e1a |
completed | March 31, 2026, 3:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce88ec84208190ab72c8411e6cc4c2 |
completed | April 2, 2026, 3:19 p.m. |
Created at: March 30, 2026, 6:14 p.m.