Triple
T671168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | African American literature |
E12972
|
entity |
| Predicate | isConcernedWith |
P11116
|
FINISHED |
| Object | representation of Black life in America |
—
|
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: representation of Black life in America | Statement: [African American literature, isConcernedWith, representation of Black life in America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isConcernedWith Context triple: [African American literature, isConcernedWith, representation of Black life in America]
-
A.
concern
chosen
Indicates that one entity is about, relates to, or is of interest or importance to another entity.
-
B.
concernsRight
Indicates that something is about or relates specifically to a legal or moral right held by an entity.
-
C.
concernsLayer
Indicates that something is related or pertains specifically to a particular layer within a layered structure or system.
-
D.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
E.
socialConcern
Indicates a relationship where an entity is concerned about, attentive to, or actively engaged with social issues, problems, or well-being.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a1b3682c8190a9b9a454480c3446 |
completed | March 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69a49d1a16c48190af89e3b078a4957e |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.