Triple
T6784002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avon, Massachusetts |
E155754
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Avon |
E155754
|
NE 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: Avon | Statement: [Avon, Massachusetts, hasName, Avon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avon Context triple: [Avon, Massachusetts, hasName, Avon]
-
A.
Avon
chosen
Avon is a small town in Norfolk County, Massachusetts, known for its suburban character and proximity to the Greater Boston area.
-
B.
Avon
Avon is a suburban town in central Connecticut known for its residential communities, schools, and proximity to the Farmington Valley.
-
C.
Avon
Avon is a suburban city in northeastern Ohio, known for its residential communities, retail development, and proximity to the Cleveland metropolitan area.
-
D.
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.
-
E.
Avon
Avon was a former non-metropolitan and ceremonial county in south-west England that existed from 1974 until its abolition in 1996.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d28bdc3c8190aa60616d89db66ed |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712d5557881909614819deb335534 |
completed | March 27, 2026, 11:29 p.m. |
Created at: March 27, 2026, 2:14 p.m.