Triple
T5178404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buffalo Springfield |
E116856
|
entity |
| Predicate | notableMember |
P10
|
FINISHED |
| Object |
Ken Koblun
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
|
E501427
|
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: Ken Koblun | Statement: [Buffalo Springfield, notableMember, Ken Koblun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Koblun Context triple: [Buffalo Springfield, notableMember, Ken Koblun]
-
A.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Jim Keltner
Jim Keltner is an American session drummer renowned for his work with artists such as John Lennon, George Harrison, Bob Dylan, and many others across rock and pop music.
-
D.
Andy Lassner
Andy Lassner is a television producer best known for his long-running work on "The Ellen DeGeneres Show" and other major daytime talk shows.
-
E.
Alan Siegel
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
- 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: Ken Koblun Triple: [Buffalo Springfield, notableMember, Ken Koblun]
Generated description
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Koblun Target entity description: Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
-
A.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Jim Keltner
Jim Keltner is an American session drummer renowned for his work with artists such as John Lennon, George Harrison, Bob Dylan, and many others across rock and pop music.
-
D.
Andy Lassner
Andy Lassner is a television producer best known for his long-running work on "The Ellen DeGeneres Show" and other major daytime talk shows.
-
E.
Alan Siegel
Alan Siegel is a film producer best known for his long-running collaboration with actor Gerard Butler on action and thriller movies.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7976339481909ece900de22064f2 |
completed | March 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee07d20208190a423a9a395ac9d32 |
completed | March 21, 2026, 6:16 p.m. |
| NEDg | Description generation | batch_69bee695358c8190801c63cff67efd1b |
completed | March 21, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bee6f91df48190adfcf47a63f4c8ef |
completed | March 21, 2026, 6:44 p.m. |
Created at: March 20, 2026, 1:45 p.m.