Triple
T15991398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fatso |
E387832
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | Friendship, Maine |
E387835
|
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: Friendship, Maine | Statement: [Fatso, setting, Friendship, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friendship, Maine Context triple: [Fatso, setting, Friendship, Maine]
-
A.
Friendship, Maine
chosen
Friendship, Maine is a small coastal town in Knox County known for its historic fishing and lobstering heritage and picturesque harbor.
-
B.
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.
-
C.
Liberty, Maine
Liberty, Maine is a small rural town in Waldo County known for its scenic lakes, forests, and outdoor recreation opportunities.
-
D.
Brownfield, Maine
Brownfield, Maine is a small rural town in western Maine known for its scenic landscapes, outdoor recreation, and proximity to the White Mountains.
-
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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157835cac81909e979f9be281f328 |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3d3ef2881909213ff608192f1ef |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:54 a.m.