Triple
T15621467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baylor Bears |
E375564
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Bruiser the Bear |
E370110
|
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: Bruiser the Bear | Statement: [Baylor Bears, mascot, Bruiser the Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruiser the Bear Context triple: [Baylor Bears, mascot, Bruiser the Bear]
-
A.
Bruiser the Bear
chosen
Bruiser the Bear is the costumed bear mascot who represents Baylor University’s athletic teams and school spirit.
-
B.
Boomer the Bear
Boomer the Bear is the costumed bear mascot who represents Missouri State University at athletic events and campus activities.
-
C.
Brisky the Bear
Brisky the Bear is the costumed bear mascot of Japan’s Hokkaido Nippon-Ham Fighters professional baseball team, known for entertaining fans at games and team events.
-
D.
Bruno the Bear
Bruno the Bear is the costumed bear mascot that represents Brown University at its athletic events and school functions.
-
E.
Bart the Bear
Bart the Bear was a famous trained Kodiak bear actor known for his prominent roles in Hollywood films and television.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9a95f08190b0013ba1428849d3 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3da754819085a6bd9876b12c65 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.