Triple
T7718478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana Tech University |
E174946
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object |
Champ
Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
|
E684396
|
NE FINISHED |
How this triple was built (4 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: [Louisiana Tech University, hasMascot, Champ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Champ Context triple: [Louisiana Tech University, hasMascot, Champ]
-
A.
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.
-
B.
Champ
Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
-
C.
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.
-
D.
The Champ
The Champ is a 1931 American drama film directed by King Vidor, renowned for its poignant story of a washed-up boxer and his devoted young son.
-
E.
Champion
"Champion" is a 1949 American film noir boxing drama directed by Mark Robson and starring Kirk Douglas as an ambitious but ruthless prizefighter.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Champ Triple: [Louisiana Tech University, hasMascot, Champ]
Generated description
Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Champ Target entity description: Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
-
A.
Champ
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 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.
-
D.
The Champ
The Champ is a 1931 American drama film directed by King Vidor, renowned for its poignant story of a washed-up boxer and his devoted young son.
-
E.
Champion
"Champion" is a 1949 American film noir boxing drama directed by Mark Robson and starring Kirk Douglas as an ambitious but ruthless prizefighter.
- F. None of above. chosen
Provenance (5 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b510650481908d65838108a2d632 |
completed | March 29, 2026, 5:13 a.m. |
| NEDg | Description generation | batch_69c8b6bfb96881908d0e82d3efa1e6e2 |
completed | March 29, 2026, 5:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8b7359cf48190b48782e2eabd5e6d |
completed | March 29, 2026, 5:23 a.m. |
Created at: March 27, 2026, 4:05 p.m.