Triple
T12862151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merrill, Maine |
E307618
|
entity |
| Predicate | sharesCountyWith |
P96061
|
FINISHED |
| Object | Smyrna, Maine |
—
|
NE NERFINISHED |
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: Smyrna, Maine | Statement: [Merrill, Maine, sharesCountyWith, Smyrna, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smyrna, Maine Context triple: [Merrill, Maine, sharesCountyWith, Smyrna, Maine]
-
A.
Smyrna, Maine
chosen
Smyrna, Maine is a small rural town located in northeastern Maine within Aroostook County, known for its agricultural character and close-knit community.
-
B.
Searsmont, Maine
Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
-
C.
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.
-
D.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
-
E.
Corinth, Maine
Corinth, Maine is a small rural town in central Maine known for its close-knit community and agricultural character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708ba74881909b16c1e2ef5115db |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:37 p.m.