Triple
T10067253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Somerset County, Maine |
E213131
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Starks, Maine |
E167476
|
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: Starks, Maine | Statement: [Somerset County, Maine, containsTown, Starks, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Starks, Maine Context triple: [Somerset County, Maine, containsTown, Starks, Maine]
-
A.
Starks, Maine
chosen
Starks, Maine is a small rural town in central Maine known for its agricultural character and location within Somerset County.
-
B.
Stetson, Maine
Stetson, Maine is a small rural town in central Maine known for its lakes, forests, and quiet residential character.
-
C.
Thorndike, Maine
Thorndike, Maine is a small rural town located in Waldo County in the central part of the state.
-
D.
Stow, Maine
Stow, Maine is a small rural town in Oxford County known for its scenic forests and proximity to the New Hampshire border in western Maine.
-
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.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff63a4c8190bb08a0428aafa189 |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d2da6b48190bdd974fa9520bc87 |
completed | May 3, 2026, 7:08 p.m. |
Created at: March 30, 2026, 8:58 p.m.