Triple
T11519481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Pegula |
E273123
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object |
Laura Pegula
Laura Pegula is a member of the Pegula family, known for their prominence in American professional sports and business through ownership stakes in major franchises.
|
E931867
|
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: Laura Pegula | Statement: [Matthew Pegula, sibling, Laura Pegula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Pegula Context triple: [Matthew Pegula, sibling, Laura Pegula]
-
A.
Kelly Pegula
Kelly Pegula is a member of the Pegula family, known for their prominent role in American professional sports ownership and business.
-
B.
Kim Pegula
Kim Pegula is an American businesswoman and sports executive who serves as co-owner and president of the Buffalo Bills and Buffalo Sabres.
-
C.
Katie Smith
Katie Smith is a Hall of Fame American basketball player and three-time WNBA champion renowned as one of the league’s greatest scorers and most versatile guards.
-
D.
Megan Mathias
Megan Mathias is known primarily as one of the children of American Olympic decathlon champion and politician Bob Mathias.
-
E.
Kristin Matheny
Kristin Matheny is known as the wife of former Major League Baseball player and manager Mike Matheny.
- 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: Laura Pegula Triple: [Matthew Pegula, sibling, Laura Pegula]
Generated description
Laura Pegula is a member of the Pegula family, known for their prominence in American professional sports and business through ownership stakes in major franchises.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Pegula Target entity description: Laura Pegula is a member of the Pegula family, known for their prominence in American professional sports and business through ownership stakes in major franchises.
-
A.
Kelly Pegula
Kelly Pegula is a member of the Pegula family, known for their prominent role in American professional sports ownership and business.
-
B.
Kim Pegula
Kim Pegula is an American businesswoman and sports executive who serves as co-owner and president of the Buffalo Bills and Buffalo Sabres.
-
C.
Katie Smith
Katie Smith is a Hall of Fame American basketball player and three-time WNBA champion renowned as one of the league’s greatest scorers and most versatile guards.
-
D.
Megan Mathias
Megan Mathias is known primarily as one of the children of American Olympic decathlon champion and politician Bob Mathias.
-
E.
Kristin Matheny
Kristin Matheny is known as the wife of former Major League Baseball player and manager Mike Matheny.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcf927081908ef89eff7ad833b0 |
completed | April 10, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6853dc47c81909d47f1047ba662e7 |
completed | April 20, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69e68fd6b6088190b24f552b5afc3f55 |
completed | April 20, 2026, 8:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e6b7a31b4081909b06bc9b6d0a1617 |
completed | April 20, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:36 p.m.