Triple
T2594579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Mohegan |
E58197
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Lake Mohegan |
E58197
|
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 Mohegan | Statement: [Lake Mohegan, hasName, Lake Mohegan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Mohegan Context triple: [Lake Mohegan, hasName, Lake Mohegan]
-
A.
Lake Mohegan
chosen
Lake Mohegan is a residential hamlet in the town of Yorktown in Westchester County, New York.
-
B.
Lake Waramaug
Lake Waramaug is a scenic glacial lake in northwestern Connecticut known for its recreational opportunities, surrounding state park, and picturesque New England setting.
-
C.
Lake Compounce
Lake Compounce is a historic amusement park and water park in Connecticut, known as one of the oldest continuously operating amusement parks in the United States.
-
D.
Lake Waban
Lake Waban is a scenic freshwater lake in Wellesley, Massachusetts, known for its walking trails and its central role in the landscape of Wellesley College.
-
E.
Oneida Lake
Oneida Lake is a large, shallow lake in central New York known for its recreational fishing, boating, and role as an important link in the region’s waterways.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd427f58c8190af1c1a9724158c96 |
completed | March 7, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83c3607c81908bb4aceca46c5392 |
completed | March 10, 2026, 2:36 a.m. |
Created at: March 6, 2026, 9:49 p.m.