Triple
T10417484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knox County, Maine |
E245557
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
St. George, Maine
St. George, Maine is a small coastal town in the Midcoast region of Maine known for its fishing heritage, scenic peninsulas, and views of the Atlantic Ocean.
|
E1126219
|
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: St. George, Maine | Statement: [Knox County, Maine, containsTown, St. George, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. George, Maine Context triple: [Knox County, Maine, containsTown, St. George, Maine]
-
A.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
-
B.
Lovell, Maine
Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
-
C.
Searsmont, Maine
Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
-
D.
Veazie, Maine
Veazie, Maine is a small residential town in eastern Maine located along the Penobscot River near the city of Bangor.
-
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. 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: St. George, Maine Triple: [Knox County, Maine, containsTown, St. George, Maine]
Generated description
St. George, Maine is a small coastal town in the Midcoast region of Maine known for its fishing heritage, scenic peninsulas, and views of the Atlantic Ocean.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: St. George, Maine Target entity description: St. George, Maine is a small coastal town in the Midcoast region of Maine known for its fishing heritage, scenic peninsulas, and views of the Atlantic Ocean.
-
A.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
-
B.
Lovell, Maine
Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
-
C.
Searsmont, Maine
Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
-
D.
Veazie, Maine
Veazie, Maine is a small residential town in eastern Maine located along the Penobscot River near the city of Bangor.
-
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. 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea1194e08190a18c3b3002147493 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b366470819093a74828e2a85116 |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6c2b7ec08190ba0b4a30cbb738e8 |
completed | May 8, 2026, 11:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6fff4f408190ac51668da19db284 |
completed | May 8, 2026, 11:21 p.m. |
Created at: April 6, 2026, 12:11 p.m.