Triple
T22142589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linden, Alabama |
E547200
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Black Belt (Alabama) |
—
|
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: Black Belt (Alabama) | Statement: [Linden, Alabama, region, Black Belt (Alabama)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Black Belt (Alabama) Context triple: [Linden, Alabama, region, Black Belt (Alabama)]
-
A.
Black Belt (Alabama)
chosen
Black Belt (Alabama) is a historically significant region of Alabama known for its fertile dark soil, large African American population, and central role in the state’s agricultural and civil rights history.
-
B.
Black, Alabama
Black, Alabama is a small rural town located in southeastern Alabama near the Florida border.
-
C.
Bryant, Alabama
Bryant, Alabama is an unincorporated community in Jackson County known for its rural character and proximity to the Tennessee state line within the Greater Chattanooga area.
-
D.
Brent, Alabama
Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
-
E.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
- 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129bf78108190b50d937917258693 |
completed | April 28, 2026, 9:42 p.m. |
Created at: April 16, 2026, 8:32 p.m.