Triple
T21453597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AL 25 |
E529279
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Wilton, 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: Wilton, Alabama | Statement: [AL 25, passesThrough, Wilton, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilton, Alabama Context triple: [AL 25, passesThrough, Wilton, Alabama]
-
A.
Wilton, Alabama
chosen
Wilton, Alabama is a small town located in Shelby County in the central part of the state.
-
B.
Waverly, Alabama
Waverly, Alabama is a small rural town in eastern Alabama known for its tight-knit community and historic Southern character.
-
C.
Milstead, Alabama
Milstead, Alabama is a small unincorporated rural community located in Macon County in the east-central part of the state.
-
D.
Wilsonville, Alabama
Wilsonville, Alabama is a small town in central Alabama known for its rural character and location within the Birmingham–Hoover metropolitan area.
-
E.
Sylvania, Alabama
Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d50b88819081a771596d0a2b2b |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:07 p.m.