Triple
T13513760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Jepsen |
E322704
|
entity |
| Predicate | succeededBy |
P78
|
FINISHED |
| Object |
William Tong
William Tong is an American attorney and politician who has served as the Attorney General of Connecticut.
|
E1044955
|
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: William Tong | Statement: [George Jepsen, succeededBy, William Tong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Tong Context triple: [George Jepsen, succeededBy, William Tong]
-
A.
Mary Kagi
Mary Kagi was the mother of abolitionist John Henry Kagi, who was a key lieutenant of John Brown during the lead-up to the American Civil War.
-
B.
George Suggs
George Suggs was an early 20th-century American Major League Baseball pitcher known for his time with teams such as the Cincinnati Reds and Baltimore Terrapins.
-
C.
Lacey Beaty
Lacey Beaty is an American politician who serves as the mayor of Beaverton, Oregon, and is known for being the city's first female mayor.
-
D.
Brad Hamilton
Brad Hamilton is a central teenage character in the 1982 coming-of-age comedy film "Fast Times at Ridgemont High," known for juggling work, relationships, and the pressures of growing up.
-
E.
Nicholas Lamont
Nicholas Lamont is an actor known for his role in the British television series "Pie in the Sky."
- 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: William Tong Triple: [George Jepsen, succeededBy, William Tong]
Generated description
William Tong is an American attorney and politician who has served as the Attorney General of Connecticut.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: William Tong Target entity description: William Tong is an American attorney and politician who has served as the Attorney General of Connecticut.
-
A.
Mary Kagi
Mary Kagi was the mother of abolitionist John Henry Kagi, who was a key lieutenant of John Brown during the lead-up to the American Civil War.
-
B.
George Suggs
George Suggs was an early 20th-century American Major League Baseball pitcher known for his time with teams such as the Cincinnati Reds and Baltimore Terrapins.
-
C.
Lacey Beaty
Lacey Beaty is an American politician who serves as the mayor of Beaverton, Oregon, and is known for being the city's first female mayor.
-
D.
Brad Hamilton
Brad Hamilton is a central teenage character in the 1982 coming-of-age comedy film "Fast Times at Ridgemont High," known for juggling work, relationships, and the pressures of growing up.
-
E.
Nicholas Lamont
Nicholas Lamont is an actor known for his role in the British television series "Pie in the Sky."
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf87ca288190a147fbdb2f90985f |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75492676c81909602745e2b6436cb |
completed | May 3, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69f7555173d08190be887e81c148192e |
completed | May 3, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f756773b9c81908250ae7ffc2d8d99 |
completed | May 3, 2026, 2:06 p.m. |
Created at: April 9, 2026, 9:44 p.m.