Triple
T19743294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Earth Lake |
E474185
|
entity |
| Predicate | isTranslationOf |
P2303
|
FINISHED |
| Object | Bde Maka Ska |
—
|
NE NERFINISHED |
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: Bde Maka Ska | Statement: [White Earth Lake, isTranslationOf, Bde Maka Ska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bde Maka Ska Context triple: [White Earth Lake, isTranslationOf, Bde Maka Ska]
-
A.
Bde Maka Ska
chosen
Bde Maka Ska is the largest lake in Minneapolis, Minnesota, popular for recreation and known as part of the city’s Chain of Lakes.
-
B.
Mucho Maas
Mucho Maas is a troubled California disc jockey and the husband of protagonist Oedipa Maas in Thomas Pynchon's novel "The Crying of Lot 49."
-
C.
Makossa
Makossa is a popular urban dance and music style from Cameroon characterized by its infectious rhythms and hip-swaying movements.
-
D.
Les Muma
Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
-
E.
Moombooldool
Moombooldool is a small rural locality in the Riverina region of New South Wales, Australia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65162f0f88190b652fff01ee23090 |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.