Triple
T4287668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico, Maine |
E97307
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Canton, Maine
Canton, Maine is a small rural town in Oxford County known for its lakes, forests, and quiet residential character in western Maine.
|
E919927
|
NE FINISHED |
How this triple was built (4 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: Canton, Maine | Statement: [Mexico, Maine, borderedBy, Canton, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canton, Maine Context triple: [Mexico, Maine, borderedBy, Canton, Maine]
-
A.
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.
-
B.
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.
-
C.
Cambridge, Maine
Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
-
D.
Knox, Maine
Knox, Maine is a small rural town located in Waldo County in the state of Maine, United States.
-
E.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Canton, Maine Triple: [Mexico, Maine, borderedBy, Canton, Maine]
Generated description
Canton, Maine is a small rural town in Oxford County known for its lakes, forests, and quiet residential character in western Maine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Canton, Maine Target entity description: Canton, Maine is a small rural town in Oxford County known for its lakes, forests, and quiet residential character in western Maine.
-
A.
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.
-
B.
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.
-
C.
Cambridge, Maine
Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
-
D.
Knox, Maine
Knox, Maine is a small rural town located in Waldo County in the state of Maine, United States.
-
E.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
- F. None of above. chosen
Provenance (5 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3505ef9fc81909c73e64bf77052ce |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5424a26688190a49c3920d0edb546 |
completed | April 19, 2026, 8:59 p.m. |
| NEDg | Description generation | batch_69e5474879088190990468d960b26739 |
completed | April 19, 2026, 9:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54eccdd3881908536ee3f9f4ef516 |
completed | April 19, 2026, 9:53 p.m. |
Created at: March 12, 2026, 11:08 p.m.