Triple
T16554342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uga XI |
E402153
|
entity |
| Predicate | hasPredecessor |
P97
|
FINISHED |
| Object | Uga X |
E402152
|
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: Uga X | Statement: [Uga XI, hasPredecessor, Uga X]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uga X Context triple: [Uga XI, hasPredecessor, Uga X]
-
A.
Uga X
chosen
Uga X is the current live bulldog mascot of the University of Georgia, continuing the long-running Uga mascot lineage for the school's athletic teams.
-
B.
Uga V
Uga V was a beloved English Bulldog who served as the live mascot of the University of Georgia Bulldogs football team.
-
C.
Uga XI
Uga XI is the current live bulldog mascot of the University of Georgia’s athletic teams, continuing the school’s long-running Uga mascot lineage.
-
D.
XUA
XUA (Cross-Enterprise User Assertion) is an IHE IT Infrastructure profile that standardizes how user identity and authentication information is securely communicated across healthcare enterprises.
-
E.
Ug
Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc737ac8190b755e2a39b6ef32b |
completed | April 18, 2026, 9:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006edbd8388190b9a96c1cc5c9119e |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:15 a.m.