Triple
T14048428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clair border station |
E338020
|
entity |
| Predicate | locatedOpposite |
P3232
|
FINISHED |
| Object | Fort Kent, Maine |
E6034
|
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: Fort Kent, Maine | Statement: [Clair border station, locatedOpposite, Fort Kent, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fort Kent, Maine Context triple: [Clair border station, locatedOpposite, Fort Kent, Maine]
-
A.
Fort Kent, Maine
chosen
Fort Kent, Maine is a small town in northern Aroostook County known for its location at the Canadian border and as a gateway to the North Maine Woods.
-
B.
Mapleton, Maine
Mapleton, Maine is a small rural town in northern Maine known for its agricultural landscape and location within Aroostook County.
-
C.
Stetson, Maine
Stetson, Maine is a small rural town in central Maine known for its lakes, forests, and quiet residential character.
-
D.
Buxton, Maine
Buxton, Maine is a small New England town in York County known for its rural character and proximity to the Portland metropolitan area.
-
E.
Pownal, Maine
Pownal, Maine is a small rural town in southern Maine known for its scenic landscapes and proximity to the Portland metropolitan area.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdefaabd0819098870522a6ce850c |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:20 p.m.