Triple
T8108842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artifact |
E189292
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Mike Krieger |
E145633
|
NE FINISHED |
How this triple was built (2 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: Mike Krieger | Statement: [Artifact, foundedBy, Mike Krieger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Krieger Context triple: [Artifact, foundedBy, Mike Krieger]
-
A.
Mike Krieger
chosen
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.
-
B.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
C.
Ken Koblun
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
-
D.
Steve Kragthorpe
Steve Kragthorpe is an American football coach best known for revitalizing the University of Tulsa’s football program in the early 2000s and later serving as head coach at the University of Louisville.
-
E.
Kevin Manthei
Kevin Manthei is an American composer known for his work on film, television, and video game scores, particularly in the animation and superhero genres.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42fbc57c81908c6be87bbc547085 |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf421875f88190a005c3ffba04dffe |
completed | April 3, 2026, 4:29 a.m. |
Created at: March 30, 2026, 5:32 p.m.