Triple
T7438729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deltona |
E171688
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object | Lake Monroe |
E412437
|
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 Monroe | Statement: [Deltona, hasLake, Lake Monroe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Monroe Context triple: [Deltona, hasLake, Lake Monroe]
-
A.
Lake Monroe
chosen
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.
-
B.
Lake Monroe
Lake Monroe is a large man-made reservoir in south-central Indiana known for boating, fishing, and outdoor recreation.
-
C.
Lake Martin
Lake Martin is a large, man-made reservoir in central Alabama known for its scenic shoreline, recreational boating, and lakeside communities.
-
D.
Lake Oscawana
Lake Oscawana is a popular recreational lake in Putnam Valley, New York, known for boating, fishing, and its scenic wooded surroundings.
-
E.
Lake Katherine
Lake Katherine is a scenic man-made lake and nature preserve in Palos Heights, Illinois, known for its walking trails, wildlife habitat, and environmental education programs.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8ac7fdaec8190a014513b8b60977b |
completed | March 29, 2026, 4:37 a.m. |
Created at: March 27, 2026, 3:13 p.m.