Triple
T5105044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavaliers |
E115070
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Cavalier |
E108224
|
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: Cavalier | Statement: [Cavaliers, mascot, Cavalier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cavalier Context triple: [Cavaliers, mascot, Cavalier]
-
A.
Cavalier
chosen
Cavalier is the costumed mascot character representing the University of Virginia’s athletic teams, typically depicted as a historical Virginia cavalryman.
-
B.
Cavalier
Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
-
C.
Bassett
Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
-
D.
Hound
Hound is a coastal civil parish in the Borough of Eastleigh in Hampshire, England, encompassing villages such as Netley and Butlocks Heath.
-
E.
Chester French
Chester French is an American indie pop duo known for their genre-blending sound, witty lyrics, and early association with producers like Pharrell Williams.
- 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7589e40c8190a46e4a1b7142be14 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba95dbd48190a7d87f3af77424e0 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:41 p.m.