Triple
T7231261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Beshear |
E154906
|
entity |
| Predicate | succeededBy |
P78
|
FINISHED |
| Object |
Matt Bevin
Matt Bevin is an American Republican politician and businessman who served as the 62nd governor of Kentucky from 2015 to 2019.
|
E650655
|
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: Matt Bevin | Statement: [Steve Beshear, succeededBy, Matt Bevin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Bevin Context triple: [Steve Beshear, succeededBy, Matt Bevin]
-
A.
Todd Haberman
Todd Haberman is a film and television composer known for his work on the drama series "9-1-1."
-
B.
Justin Wilcox
Justin Wilcox is an American college football coach best known as the head coach of the University of California, Berkeley Golden Bears.
-
C.
Keith Moseley
Keith Moseley is an American bassist best known as a founding member of the jam band The String Cheese Incident.
-
D.
James Whitaker
James Whitaker is a film cinematographer known for his work on feature films such as the comedy-drama "Troop Zero."
-
E.
Bill Pence
Bill Pence was an American film executive and co-founder of the influential Telluride Film Festival, known for shaping the landscape of international film exhibition and appreciation.
- 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: Matt Bevin Triple: [Steve Beshear, succeededBy, Matt Bevin]
Generated description
Matt Bevin is an American Republican politician and businessman who served as the 62nd governor of Kentucky from 2015 to 2019.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt Bevin Target entity description: Matt Bevin is an American Republican politician and businessman who served as the 62nd governor of Kentucky from 2015 to 2019.
-
A.
Todd Haberman
Todd Haberman is a film and television composer known for his work on the drama series "9-1-1."
-
B.
Justin Wilcox
Justin Wilcox is an American college football coach best known as the head coach of the University of California, Berkeley Golden Bears.
-
C.
Keith Moseley
Keith Moseley is an American bassist best known as a founding member of the jam band The String Cheese Incident.
-
D.
James Whitaker
James Whitaker is a film cinematographer known for his work on feature films such as the comedy-drama "Troop Zero."
-
E.
Bill Pence
Bill Pence was an American film executive and co-founder of the influential Telluride Film Festival, known for shaping the landscape of international film exhibition and appreciation.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea0f09648190b285993556f704d5 |
completed | March 27, 2026, 8:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc22a39481909a2f38014260f302 |
completed | March 28, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_69c7cd95c8c48190aa4c7d086f03bc0f |
completed | March 28, 2026, 12:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ce1b5e0081908d8e68fb1c0bfd3e |
completed | March 28, 2026, 12:48 p.m. |
Created at: March 27, 2026, 2:54 p.m.