Triple
T14429270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanford, Maine |
E357777
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Lebanon, 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: Lebanon, Maine | Statement: [Sanford, Maine, borderedBy, Lebanon, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lebanon, Maine Context triple: [Sanford, Maine, borderedBy, Lebanon, Maine]
-
A.
Lebanon, Maine
chosen
Lebanon, Maine is a small rural town in southwestern Maine known for its forests, lakes, and proximity to the New Hampshire border.
-
B.
Levant, Maine
Levant, Maine is a small rural town located in Penobscot County in central Maine, known for its agricultural character and close proximity to the city of Bangor.
-
C.
Warren, Maine
Warren, Maine is a small town in Knox County known for its rural character and location along the St. George River in midcoast Maine.
-
D.
Hope, Maine
Hope, Maine is a small rural town in coastal Knox County known for its scenic lakes, rolling hills, and quiet New England character.
-
E.
Gray, Maine
Gray, Maine is a small New England town in southern Maine known for its rural character, proximity to Portland, and the Maine Wildlife Park.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91154de881909266ae88d1545685 |
completed | April 14, 2026, 7:10 p.m. |
Created at: April 10, 2026, 1:18 a.m.