Triple
T10245148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melina Matsoukas |
E240193
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Issa Rae |
E126871
|
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: Issa Rae | Statement: [Melina Matsoukas, workedWith, Issa Rae]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Issa Rae Context triple: [Melina Matsoukas, workedWith, Issa Rae]
-
A.
Issa Rae
chosen
Issa Rae is an American actress, writer, and producer best known for creating and starring in the HBO series "Insecure."
-
B.
Amber Ruffin
Amber Ruffin is an American comedian, writer, and television host best known for her work on "Late Night with Seth Meyers" and for creating and starring in "The Amber Ruffin Show."
-
C.
Sanaa Chappelle
Sanaa Chappelle is an American child actress best known for appearing alongside her father, comedian Dave Chappelle, in the film "A Star Is Born" (2018).
-
D.
Tiffany Haddish
Tiffany Haddish is an American stand-up comedian and actress known for her breakout role in "Girls Trip" and her energetic, unfiltered comedic style.
-
E.
Regina Hall
Regina Hall is an American actress and comedian known for her roles in films such as the Scary Movie series, Girls Trip, and numerous television comedies.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22be0208190b671a4e3f81d11b8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f79c20e08190928d061b3d4b4e47 |
completed | April 9, 2026, 12:49 a.m. |
Created at: April 6, 2026, 11:26 a.m.