Triple
T10831559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Souadabscook Stream |
E255630
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Carmel, Maine |
E326187
|
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: Carmel, Maine | Statement: [Souadabscook Stream, flowsThrough, Carmel, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmel, Maine Context triple: [Souadabscook Stream, flowsThrough, Carmel, Maine]
-
A.
Carmel, Maine
chosen
Carmel, Maine is a small rural town in Penobscot County known for its close-knit community and proximity to the Bangor metropolitan area.
-
B.
Burnham, Maine
Burnham, Maine is a small rural town in central Maine known for its lakes, forests, and quiet residential character.
-
C.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
-
D.
Searsmont, Maine
Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
-
E.
Camden, Maine
Camden, Maine is a picturesque coastal town in midcoast Maine known for its scenic harbor, historic downtown, and access to Camden Hills State Park.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d744222288819093258b452569acab |
completed | April 9, 2026, 6:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180bd1e5c8190a6a96581ce8a37de |
completed | May 11, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:19 p.m.