Triple
T21878409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel Stile |
E540212
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Ambleside |
—
|
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: Ambleside | Statement: [Chapel Stile, nearbyPlace, Ambleside]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ambleside Context triple: [Chapel Stile, nearbyPlace, Ambleside]
-
A.
Ambleside
chosen
Ambleside is a popular town in England’s Lake District, known as a base for walking, boating on nearby Lake Windermere, and exploring the surrounding fells.
-
B.
Valley Head
Valley Head is a small town in DeKalb County, northeastern Alabama, known for its scenic location near Lookout Mountain.
-
C.
AMBLESIDE
AMBLESIDE is a picturesque town in England’s Lake District, known as a popular base for walking, climbing, and exploring the surrounding fells and lakes.
-
D.
Simonswood
Simonswood is a small rural village and civil parish in Lancashire, England, known for its agricultural landscape and quiet countryside character.
-
E.
Wylandville
Wylandville is a small unincorporated community located in Washington County, Pennsylvania, United States.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118e42c108190b6308016655c429e |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 16, 2026, 7:03 p.m.