Triple
T3153988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meagan Good |
E65940
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Regina Hall |
E65704
|
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: Regina Hall | Statement: [Meagan Good, workedWith, Regina Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Regina Hall Context triple: [Meagan Good, workedWith, Regina Hall]
-
A.
Regina Hall
chosen
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.
-
B.
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.
-
C.
Wanda Sykes
Wanda Sykes is an American stand-up comedian, actress, and writer known for her sharp, outspoken humor and roles in television, film, and voice acting.
-
D.
Issa Rae
Issa Rae is an American actress, writer, and producer best known for creating and starring in the HBO series "Insecure."
-
E.
Melissa McCarthy
Melissa McCarthy is an American actress and comedian known for her breakout comedic role in "Bridesmaids" and subsequent work in film and television.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5e7f4688190b477186254f8a572 |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b261fd69dc8190a6005d1af2d12a11 |
completed | March 12, 2026, 6:49 a.m. |
Created at: March 8, 2026, 3:05 p.m.