Triple
T3174655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grizz Gaming |
E66432
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Grizz |
E158113
|
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: Grizz | Statement: [Grizz Gaming, shortName, Grizz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grizz Context triple: [Grizz Gaming, shortName, Grizz]
-
A.
Grizz (Grizzlies mascot)
chosen
Grizz is the energetic and entertaining bear mascot of the NBA’s Memphis Grizzlies, known for hyping up crowds with stunts, dances, and fan interactions at games.
-
B.
Nanooks
Nanooks is the nickname for the University of Alaska Fairbanks athletic teams, representing the school in NCAA competition.
-
C.
Bronco
Bronco is a line of rugged sport-utility vehicles produced by Ford, known for their off-road capability and iconic boxy styling.
-
D.
Blitzen
Blitzen is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
-
E.
Cougars
Cougars is the nickname used by the former American Basketball Association team known as the Carolina Cougars.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada670c800819098937783e2b05c7a |
completed | March 8, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235f16e60819091cbdb76130ecc40 |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.