Triple
T17664192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 233 |
E440329
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Somesville, Maine |
—
|
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: Somesville, Maine | Statement: [Maine State Route 233, connects, Somesville, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Somesville, Maine Context triple: [Maine State Route 233, connects, Somesville, Maine]
-
A.
Somesville, Maine
chosen
Somesville, Maine is a historic village on Mount Desert Island known for its picturesque setting, classic New England charm, and proximity to Acadia National Park.
-
B.
Woodville, Maine
Woodville, Maine is a small rural town located in Penobscot County in the central part of the state.
-
C.
Searsmont, Maine
Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
-
D.
Montville, Maine
Montville, Maine is a small rural town in central Maine known for its forests, farms, and quiet, scenic countryside.
-
E.
Shapleigh, Maine
Shapleigh, Maine is a small rural town in southwestern Maine known for its forests, lakes, and outdoor recreation.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea7f0ec81908eff43aa845584af |
completed | April 19, 2026, 5:56 a.m. |
Created at: April 10, 2026, 9:54 a.m.