Triple
T22288505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machine |
E550926
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Chicago Machine |
—
|
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: Chicago Machine | Statement: [Machine, fullName, Chicago Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chicago Machine Context triple: [Machine, fullName, Chicago Machine]
-
A.
Chicago Machine
chosen
Chicago Machine was a professional field lacrosse team that competed in Major League Lacrosse and was based in the Chicago metropolitan area.
-
B.
Chicago Sons
Chicago Sons is an American sitcom that aired in the late 1990s, focusing on the comedic lives of three brothers living in Chicago.
-
C.
Chicago-Rillas
"Chicago-Rillas" is a song by the rapper Blue Collar.
-
D.
Chicago Star
Chicago Star was a left-leaning, progressive newspaper published in Chicago in the mid-1940s that featured political commentary, labor issues, and cultural coverage.
-
E.
Chicago Winds
Chicago Winds was a short-lived professional American football franchise based in Chicago that competed in the World Football League during the 1970s.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15609854c81908adb7681cff2c404 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 16, 2026, 8:41 p.m.