Triple
T20810378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avon Lake |
E512280
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Avon |
—
|
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: Avon | Statement: [Avon Lake, adjacentTo, Avon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avon Context triple: [Avon Lake, adjacentTo, Avon]
-
A.
Avon
Avon is a suburban town in central Connecticut known for its residential communities, schools, and proximity to the Farmington Valley.
-
B.
Avon
Avon is a global beauty and personal care company best known for its direct-selling model and extensive range of cosmetics, skincare, and fragrance products.
-
C.
Avon
Avon is a suburban town in Hendricks County, Indiana, known for its residential communities and proximity to Indianapolis.
-
D.
Avon
Avon is a small town in Norfolk County, Massachusetts, known for its suburban character and proximity to the Greater Boston area.
-
E.
Avon
chosen
Avon is a suburban city in northeastern Ohio, known for its residential communities, retail development, and proximity to the Cleveland metropolitan area.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d27a4881908b34679385d8b94b |
completed | April 21, 2026, 12:20 a.m. |
Created at: April 16, 2026, 12:40 p.m.