Triple
T7675635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Klein |
E173852
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Ray Fair
Ray Fair is an American economist known for his work in macroeconometric modeling, forecasting, and the analysis of economic policy.
|
E681559
|
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: Ray Fair | Statement: [Lawrence Klein, notableStudent, Ray Fair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ray Fair Context triple: [Lawrence Klein, notableStudent, Ray Fair]
-
A.
Dan Foy
Dan Foy is an American local politician who serves as the mayor of Burbank, Illinois.
-
B.
Dan Rydell
Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
-
C.
Ray Meyer
Ray Meyer was a Hall of Fame college basketball coach best known for transforming DePaul University into a national powerhouse during his long tenure.
-
D.
Ken Scott
Ken Scott is a Canadian screenwriter and director known for films such as "Starbuck," "Delivery Man," and "The Grand Seduction."
-
E.
Terry Gilkyson
Terry Gilkyson was an American folk singer and songwriter best known for penning classic Disney songs, including "The Bare Necessities" from The Jungle Book.
- 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: Ray Fair Triple: [Lawrence Klein, notableStudent, Ray Fair]
Generated description
Ray Fair is an American economist known for his work in macroeconometric modeling, forecasting, and the analysis of economic policy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ray Fair Target entity description: Ray Fair is an American economist known for his work in macroeconometric modeling, forecasting, and the analysis of economic policy.
-
A.
Dan Foy
Dan Foy is an American local politician who serves as the mayor of Burbank, Illinois.
-
B.
Dan Rydell
Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
-
C.
Ray Meyer
Ray Meyer was a Hall of Fame college basketball coach best known for transforming DePaul University into a national powerhouse during his long tenure.
-
D.
Ken Scott
Ken Scott is a Canadian screenwriter and director known for films such as "Starbuck," "Delivery Man," and "The Grand Seduction."
-
E.
Terry Gilkyson
Terry Gilkyson was an American folk singer and songwriter best known for penning classic Disney songs, including "The Bare Necessities" from The Jungle Book.
- 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701e333f08190a9ee87080c6d0118 |
completed | March 27, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a23ba62881908fcdcf2ffcf6d41d |
completed | March 29, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_69c8a49262ec81908f3b45031994d128 |
completed | March 29, 2026, 4:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8a50df2a88190b5f7db0afea96fc3 |
completed | March 29, 2026, 4:05 a.m. |
Created at: March 27, 2026, 4:01 p.m.