Triple
T33765988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiswana Browne |
E865229
|
entity |
| Predicate | mainThemeAssociation |
P176949
|
FINISHED |
| Object | race and class in African-American communities |
—
|
LITERAL 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: race and class in African-American communities | Statement: [Kiswana Browne, mainThemeAssociation, race and class in African-American communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainThemeAssociation Context triple: [Kiswana Browne, mainThemeAssociation, race and class in African-American communities]
-
A.
primaryThemeAssociation
Indicates that one entity is the main or central theme associated with another entity.
-
B.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
C.
coreThemeAssociation
chosen
Indicates a primary, central, or defining thematic relationship between two entities, where one serves as a core theme of the other.
-
D.
associatedThemeElements
Indicates a relationship where certain elements are linked to, or grouped under, a particular theme as its related components.
-
E.
hasThemeRelationship
Indicates a relationship where one entity is thematically related to, or centered around, another entity as its main subject or topic.
- F. None of above.
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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 1, 2026, 1:45 a.m.