Triple
T14252699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saco, Maine |
E353308
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Dayton, Maine |
E527164
|
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: Dayton, Maine | Statement: [Saco, Maine, borders, Dayton, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dayton, Maine Context triple: [Saco, Maine, borders, Dayton, Maine]
-
A.
Dayton, Maine
chosen
Dayton, Maine is a small rural town in southern Maine known for its quiet residential character and location along the Saco River in York County.
-
B.
Dresden, Maine
Dresden, Maine is a small rural town in Lincoln County known for its historic character and scenic location along the Kennebec River.
-
C.
Durham, Maine
Durham, Maine is a small rural town in southern Maine known for its quiet residential character and proximity to the Lewiston–Auburn and Portland metropolitan areas.
-
D.
Frankfort, Maine
Frankfort, Maine is a small rural town in Waldo County known for its scenic setting along the Penobscot River and its historic New England character.
-
E.
Trenton, Maine
Trenton, Maine is a small coastal town in Hancock County that serves as a gateway to Mount Desert Island and Acadia National Park.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6297f38c819090d7c7fd8bfa2e9e |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05e64fe7408190914a43f7c44872d7 |
completed | May 14, 2026, 3:12 p.m. |
Created at: April 10, 2026, 1:09 a.m.