Triple
T2291597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl VII |
E51515
|
entity |
| Predicate | MVP |
P2630
|
FINISHED |
| Object |
Jake Scott
Jake Scott was an American NFL safety best known for his standout play with the Miami Dolphins in the early 1970s, including their perfect season.
|
E255857
|
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: Jake Scott | Statement: [Super Bowl VII, MVP, Jake Scott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Scott Context triple: [Super Bowl VII, MVP, Jake Scott]
-
A.
Jake Scott
Jake Scott is a British film and music video director known for his work with prominent rock bands and artists.
-
B.
Ed Scott
Ed Scott is a technology entrepreneur best known as a co-founder of BEA Systems, a major enterprise software company later acquired by Oracle.
-
C.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Tom Mason
Tom Mason is the former history professor turned resistance leader who serves as the central protagonist in the post-apocalyptic alien invasion series "Falling Skies."
- 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: Jake Scott Triple: [Super Bowl VII, MVP, Jake Scott]
Generated description
Jake Scott was an American NFL safety best known for his standout play with the Miami Dolphins in the early 1970s, including their perfect season.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jake Scott Target entity description: Jake Scott was an American NFL safety best known for his standout play with the Miami Dolphins in the early 1970s, including their perfect season.
-
A.
Jake Scott
Jake Scott is a British film and music video director known for his work with prominent rock bands and artists.
-
B.
Ed Scott
Ed Scott is a technology entrepreneur best known as a co-founder of BEA Systems, a major enterprise software company later acquired by Oracle.
-
C.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Tom Mason
Tom Mason is the former history professor turned resistance leader who serves as the central protagonist in the post-apocalyptic alien invasion series "Falling Skies."
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5b3d4988190bceb3dffa9734f4b |
completed | March 7, 2026, 6:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae8952322c81909d58b89139f51a27 |
completed | March 9, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_69ae8d5b13bc819094d0cc02736ba6b5 |
completed | March 9, 2026, 9:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae8dd17a0081908c08d344178674d5 |
completed | March 9, 2026, 9:07 a.m. |
Created at: March 4, 2026, 7:48 p.m.