Triple
T20028653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spring Hill College |
E495058
|
entity |
| Predicate | hasAthleticNickname |
P55
|
FINISHED |
| Object | Badgers |
—
|
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: Badgers | Statement: [Spring Hill College, hasAthleticNickname, Badgers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badgers Context triple: [Spring Hill College, hasAthleticNickname, Badgers]
-
A.
Badgers
Badgers is the nickname for the athletic teams representing the University of Wisconsin–Madison in collegiate sports.
-
B.
Badgers
chosen
Badgers is the nickname and mascot for the athletic teams representing Spring Hill College.
-
C.
Badger
Badger is the NATO reporting name for the Soviet-era Tupolev Tu-16, a twin-engine jet strategic bomber widely used during the Cold War.
-
D.
Badger
Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
-
E.
Badger
Badger is a British rock band best known for its early-1970s progressive rock sound and connections to members of the band Yes.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628f67e081909b9e69dfbe2127ce |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.