Triple
T38393341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Stark |
E899786
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | African American woman character |
C4883
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: African American woman character Context triple: [Vera Stark, instanceOf, African American woman character]
-
A.
African-American woman
chosen
An African-American woman is a female-identifying person of African descent whose cultural, historical, and social experiences are shaped by both Black and American identities.
-
B.
African-American character
An African-American character is a fictional or narrative figure whose identity, culture, and experiences are rooted in the historical and contemporary realities of African-descended people in the United States.
-
C.
African-American character in film
An African-American character in film is a fictional or dramatized Black individual whose identity, experiences, and representation reflect aspects of African-American culture, history, and social context within the narrative.
-
D.
African American literary character
An African American literary character is a fictional person of African American heritage whose experiences, identity, and perspectives are depicted within a literary work, often engaging with themes of race, culture, history, and social justice.
-
E.
African-American
African-American refers to a Black person in the United States who has ancestral origins in Africa, often specifically linked to the historical experiences and cultural heritage of the African diaspora in America.
- F. None of above.
Provenance (1 batch)
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_69f76e5c9b808190b486523f5c2f817d |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:31 p.m.