Triple
T12862445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth Hasselbeck |
E307627
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Hasselbeck
Hasselbeck is a surname most prominently associated with American television personality and former "The View" co-host Elisabeth Hasselbeck and her family.
|
E1007189
|
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: Hasselbeck | Statement: [Elisabeth Hasselbeck, familyName, Hasselbeck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasselbeck Context triple: [Elisabeth Hasselbeck, familyName, Hasselbeck]
-
A.
Tim Hasselbeck
Tim Hasselbeck is a former NFL quarterback who later became a football analyst and commentator for ESPN.
-
B.
Sarah Hasselbeck
Sarah Hasselbeck is known as the wife of former NFL quarterback and sports analyst Matt Hasselbeck.
-
C.
John Beck
John Beck is a film producer best known for his work on the classic 1950 comedy-fantasy movie "Harvey."
-
D.
Don Hasselbeck
Don Hasselbeck is a former American football tight end who played in the NFL, notably for the New England Patriots, during the late 1970s and early 1980s.
-
E.
Drew Bledsoe
Drew Bledsoe is a former NFL quarterback best known for his long tenure with the New England Patriots and for paving the way for Tom Brady’s rise after Bledsoe’s injury.
- 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: Hasselbeck Triple: [Elisabeth Hasselbeck, familyName, Hasselbeck]
Generated description
Hasselbeck is a surname most prominently associated with American television personality and former "The View" co-host Elisabeth Hasselbeck and her family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hasselbeck Target entity description: Hasselbeck is a surname most prominently associated with American television personality and former "The View" co-host Elisabeth Hasselbeck and her family.
-
A.
Tim Hasselbeck
Tim Hasselbeck is a former NFL quarterback who later became a football analyst and commentator for ESPN.
-
B.
Sarah Hasselbeck
Sarah Hasselbeck is known as the wife of former NFL quarterback and sports analyst Matt Hasselbeck.
-
C.
John Beck
John Beck is a film producer best known for his work on the classic 1950 comedy-fantasy movie "Harvey."
-
D.
Don Hasselbeck
Don Hasselbeck is a former American football tight end who played in the NFL, notably for the New England Patriots, during the late 1970s and early 1980s.
-
E.
Drew Bledsoe
Drew Bledsoe is a former NFL quarterback best known for his long tenure with the New England Patriots and for paving the way for Tom Brady’s rise after Bledsoe’s injury.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708ba74881909b16c1e2ef5115db |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bade6ec81908e3123b96837f104 |
completed | May 3, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69f69dad1f9c8190b48c40f49dbd396d |
completed | May 3, 2026, 12:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69e5fd19c819082f9fe0d26c56c9a |
completed | May 3, 2026, 1:01 a.m. |
Created at: April 9, 2026, 5:37 p.m.