Triple
T13160656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bde Maka Ska |
E312716
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Lake Calhoun |
E80133
|
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 Calhoun | Statement: [Bde Maka Ska, formerName, Lake Calhoun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Calhoun Context triple: [Bde Maka Ska, formerName, Lake Calhoun]
-
A.
Lake Calhoun (Bde Maka Ska)
chosen
Lake Calhoun (Bde Maka Ska) is the largest lake in Minneapolis, Minnesota, popular for recreation and known for its Dakota name reflecting the area’s Indigenous heritage.
-
B.
Bay Lake
Bay Lake is a natural lake in Central Florida located near the Walt Disney World Resort.
-
C.
Tonka Bay
Tonka Bay is a small lakeside city in Minnesota situated on the shores of Lake Minnetonka.
-
D.
Lake Harriet
Lake Harriet is a popular urban lake in Minneapolis known for its beaches, walking and biking paths, and lakeside bandshell hosting concerts and community events.
-
E.
Lake Park
Lake Park is a historic, Frederick Law Olmsted–designed public park in Milwaukee, Wisconsin, known for its scenic bluffs, trails, and views of Lake Michigan.
- 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_69f73055f0748190863f30b7771e801e |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:12 p.m.