Triple
T3998286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Rozelle |
E87149
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Jane Rozelle
Jane Rozelle was the wife of longtime NFL commissioner Pete Rozelle and a figure in American sports social circles during his tenure.
|
E456888
|
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: Jane Rozelle | Statement: [Pete Rozelle, spouse, Jane Rozelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Rozelle Context triple: [Pete Rozelle, spouse, Jane Rozelle]
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Rochelle Humes
Rochelle Humes is a British singer, television presenter, and entrepreneur best known as a member of the girl group The Saturdays and for hosting various UK TV shows.
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Tricia O'Kelley
Tricia O'Kelley is an American actress best known for her comedic television roles, particularly in popular sitcoms.
-
E.
Liz Sherman
Liz Sherman is a powerful pyrokinetic human and key member of the Bureau for Paranormal Research and Defense in the Hellboy comic and film series.
- 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: Jane Rozelle Triple: [Pete Rozelle, spouse, Jane Rozelle]
Generated description
Jane Rozelle was the wife of longtime NFL commissioner Pete Rozelle and a figure in American sports social circles during his tenure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jane Rozelle Target entity description: Jane Rozelle was the wife of longtime NFL commissioner Pete Rozelle and a figure in American sports social circles during his tenure.
-
A.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
B.
Rochelle Humes
Rochelle Humes is a British singer, television presenter, and entrepreneur best known as a member of the girl group The Saturdays and for hosting various UK TV shows.
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Tricia O'Kelley
Tricia O'Kelley is an American actress best known for her comedic television roles, particularly in popular sitcoms.
-
E.
Liz Sherman
Liz Sherman is a powerful pyrokinetic human and key member of the Bureau for Paranormal Research and Defense in the Hellboy comic and film series.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdf9f26be48190bf21b252a922ca69 |
completed | March 21, 2026, 1:52 a.m. |
| NEDg | Description generation | batch_69bdfba6f8e08190ad6c802ec1cb5ce2 |
completed | March 21, 2026, 2 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdfc6ac91c819090776365d3dc05d4 |
completed | March 21, 2026, 2:03 a.m. |
Created at: March 9, 2026, 3:34 p.m.