Triple
T20157181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEN/Jean Stein Book Award |
E491601
|
entity |
| Predicate | notableWinner |
P2766
|
FINISHED |
| Object | Yaa Gyasi |
—
|
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: Yaa Gyasi | Statement: [PEN/Jean Stein Book Award, notableWinner, Yaa Gyasi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yaa Gyasi Context triple: [PEN/Jean Stein Book Award, notableWinner, Yaa Gyasi]
-
A.
Yaa Gyasi
chosen
Yaa Gyasi is a Ghanaian-American novelist best known for her acclaimed debut novel "Homegoing," which explores the legacy of slavery across generations.
-
B.
Gyasi
Gyasi is a masculine given name most notably borne by American professional soccer player Gyasi Zardes.
-
C.
Jesmyn
Jesmyn is a feminine given name most notably borne by the acclaimed American novelist Jesmyn Ward.
-
D.
Amma Asante
Amma Asante is a British filmmaker and former actress known for directing socially conscious, character-driven dramas such as the historical film "Belle."
-
E.
Gloria Naylor
Gloria Naylor was an American novelist acclaimed for her powerful portrayals of African American women’s lives and communities in works such as "The Women of Brewster Place."
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.