Triple
T6915056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmore County |
E160028
|
entity |
| Predicate | hasReservoir |
P1025
|
FINISHED |
| Object | Lake Martin |
E160029
|
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: Lake Martin | Statement: [Elmore County, hasReservoir, Lake Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Martin Context triple: [Elmore County, hasReservoir, Lake Martin]
-
A.
Lake Martin
chosen
Lake Martin is a large, man-made reservoir in central Alabama known for its scenic shoreline, recreational boating, and lakeside communities.
-
B.
Lake Monroe
Lake Monroe is a large freshwater lake in central Florida that serves as a prominent widening of the St. Johns River and a key recreational and ecological area.
-
C.
Lake Monroe
Lake Monroe is a large man-made reservoir in south-central Indiana known for boating, fishing, and outdoor recreation.
-
D.
Lake Barkley
Lake Barkley is a large reservoir in western Kentucky and Tennessee known for boating, fishing, and recreation as part of the Land Between the Lakes region.
-
E.
Lake Lurleen
Lake Lurleen is a reservoir in Tuscaloosa County, Alabama, best known as the central feature and namesake of Lake Lurleen 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9dda4108190a79a7841b0658a4d |
completed | March 27, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7942be8708190bad44a9966884515 |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:26 p.m.