Triple
T15449403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mavs Man |
E370107
|
entity |
| Predicate | hasCoMascot |
P38976
|
FINISHED |
| Object | Champ |
E76222
|
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: Champ | Statement: [Mavs Man, hasCoMascot, Champ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Champ Context triple: [Mavs Man, hasCoMascot, Champ]
-
A.
Champ
chosen
Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
-
B.
Champ
Champ is a supporting character in the action-spy film "Kingsman: The Golden Circle," serving as a high-ranking member of the American Statesman organization.
-
C.
Champ
Champ is the nickname of Champ Clark, an influential early 20th-century American Democratic politician who served as Speaker of the U.S. House of Representatives.
-
D.
Champ
Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
-
E.
Champ Kind
Champ Kind is a loud, boisterous sportscaster and member of the Channel 4 news team in the comedy film "Anchorman: The Legend of Ron Burgundy," known for his over-the-top enthusiasm and catchphrases.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef9334c81908541e231b43eb012 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b1e9688190a283dbc552072ce0 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.