Triple
T10705965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 139 |
E252404
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Monroe, Maine |
E848961
|
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: Monroe, Maine | Statement: [Maine State Route 139, passesThrough, Monroe, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monroe, Maine Context triple: [Maine State Route 139, passesThrough, Monroe, Maine]
-
A.
Monroe, Maine
chosen
Monroe, Maine is a small rural town in Waldo County known for its quiet countryside and close-knit community in central coastal Maine.
-
B.
Madison, Maine
Madison, Maine is a small town in central Maine known for its rural character, historic mill industry, and location along the Kennebec River.
-
C.
Clinton, Maine
Clinton, Maine is a small rural town in central Maine known for its agricultural character and location along the Sebasticook River.
-
D.
Fairfield, Maine
Fairfield, Maine is a small town in Somerset County known for its rural character, proximity to the Kennebec River, and role as part of the greater Waterville area in central Maine.
-
E.
Washington, Maine
Washington, Maine is a small rural town in Knox County known for its lakes, forests, and quiet New England character.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddfbed48190810bb3faee473fde |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dbf2567c81909ab6054ade27afac |
completed | May 10, 2026, 7:26 p.m. |
Created at: April 8, 2026, 9:12 p.m.