Triple
T230613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minneapolis–Saint Paul |
E4402
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Minneapolis |
E13441
|
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: Minneapolis | Statement: [Minneapolis–Saint Paul, hasPart, Minneapolis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minneapolis Context triple: [Minneapolis–Saint Paul, hasPart, Minneapolis]
-
A.
Minneapolis
chosen
Minneapolis is a major city in Minnesota known for its large and historically significant Norwegian American community, vibrant arts scene, and numerous lakes.
-
B.
Minneapolis–Saint Paul
Minneapolis–Saint Paul is a major metropolitan area in Minnesota known for its twin cities, cultural institutions, and economic significance in the Upper Midwest.
-
C.
Duluth
Duluth is a major port city in northeastern Minnesota known for its shipping industry, scenic Lake Superior shoreline, and role as a regional transportation hub.
-
D.
Delano
Delano is the middle name of Franklin D. Roosevelt, the 32nd president of the United States.
-
E.
Milwaukee
Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25cadae1c8190be0e8dcf33351187 |
completed | Feb. 28, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a37952cbbc8190afd920510408fd31 |
completed | Feb. 28, 2026, 11:25 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.