Triple
T13160591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minneapolis park system |
E312714
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lake Nokomis |
E86431
|
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 Nokomis | Statement: [Minneapolis park system, hasPart, Lake Nokomis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Nokomis Context triple: [Minneapolis park system, hasPart, Lake Nokomis]
-
A.
Lake Nokomis
chosen
Lake Nokomis is a popular urban lake in Minneapolis known for its beaches, recreational activities, and surrounding parkland.
-
B.
Lake Minnetonka
Lake Minnetonka is a large, popular recreational lake in the western suburbs of the Minneapolis–Saint Paul metropolitan area in Minnesota, known for boating, fishing, and lakeside communities.
-
C.
Lake Vermilion
Lake Vermilion is a large, scenic freshwater lake in northeastern Minnesota known for its fishing, boating, and extensive shoreline dotted with cabins and resorts.
-
D.
Black Lake
Black Lake is a small inland lake located in Norton Shores, Michigan, known for local recreation and natural scenery.
-
E.
Black Lake
Black Lake is a freshwater lake in Thurston County, Washington, known for recreation such as boating and fishing amid a largely residential and forested shoreline.
- 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_69f7941e0560819080eee43a9ed0e1bb |
completed | May 3, 2026, 6:29 p.m. |
Created at: April 9, 2026, 9:12 p.m.