Triple
T464653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginger Rogers |
E8417
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Jack Briggs
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
|
E108494
|
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: Jack Briggs | Statement: [Ginger Rogers, spouse, Jack Briggs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Briggs Context triple: [Ginger Rogers, spouse, Jack Briggs]
-
A.
Conrad Riggs
Conrad Riggs is a television producer best known for his executive production work on major reality TV franchises, including "The Apprentice."
-
B.
Douglas Kirk
Douglas Kirk is an individual notable enough to be recognized as a prominent bearer of the surname Kirk.
-
C.
Keith Fraase
Keith Fraase is a film editor best known for his work on the movie "Chappaquiddick."
-
D.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
E.
Michael Klingensmith
Michael Klingensmith is an American media executive best known for helping launch and lead major magazine brands, including playing a key role in the creation of Entertainment Weekly.
- 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: Jack Briggs Triple: [Ginger Rogers, spouse, Jack Briggs]
Generated description
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jack Briggs Target entity description: Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
-
A.
Conrad Riggs
Conrad Riggs is a television producer best known for his executive production work on major reality TV franchises, including "The Apprentice."
-
B.
Douglas Kirk
Douglas Kirk is an individual notable enough to be recognized as a prominent bearer of the surname Kirk.
-
C.
Keith Fraase
Keith Fraase is a film editor best known for his work on the movie "Chappaquiddick."
-
D.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
E.
Michael Klingensmith
Michael Klingensmith is an American media executive best known for helping launch and lead major magazine brands, including playing a key role in the creation of Entertainment Weekly.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd5b6b48190ae23968135cf6417 |
completed | Feb. 28, 2026, 1:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf473e48819095390a5904429a9c |
completed | March 4, 2026, 6:20 a.m. |
| NEDg | Description generation | batch_69a7d063fe8c81909a32afaf2798297f |
completed | March 4, 2026, 6:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7d0c6a14c81909d98c648aef4e87b |
completed | March 4, 2026, 6:27 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.