Triple
T13160654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bde Maka Ska |
E312716
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Chain of Lakes |
E312713
|
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: Chain of Lakes | Statement: [Bde Maka Ska, partOf, Chain of Lakes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chain of Lakes Context triple: [Bde Maka Ska, partOf, Chain of Lakes]
-
A.
Chain of Lakes
chosen
Chain of Lakes is a popular interconnected group of urban lakes in Minneapolis, Minnesota, known for recreation, scenic trails, and surrounding parkland.
-
B.
Chain of Lakes
Chain of Lakes is a connected system of freshwater lakes in central Florida known for recreation, boating, and scenic waterfront communities.
-
C.
Chain O’Lakes
Chain O’Lakes is a popular interconnected system of lakes in northeastern Illinois known for boating, fishing, and recreational tourism.
-
D.
City of Lakes
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
-
E.
City of Lakes
City of Lakes is a popular nickname for Thane, a city in Maharashtra, India, known for its numerous lakes and scenic waterfronts.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c0971008190869e9de710f4c579 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaf2ae688190b3484989791977ce |
completed | May 3, 2026, 6:28 a.m. |
Created at: April 9, 2026, 9:12 p.m.