Triple
T15674883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tripper Harrison |
E377414
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Len Blum |
—
|
NE NERFINISHED |
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: Len Blum | Statement: [Tripper Harrison, createdBy, Len Blum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Len Blum Context triple: [Tripper Harrison, createdBy, Len Blum]
-
A.
Len Blum
chosen
Len Blum is a Canadian screenwriter known for his work on numerous comedy films, including the 2006 reboot of The Pink Panther.
-
B.
Don Blum
Don Blum is an American rock drummer best known for his work with the Detroit garage rock band The Von Bondies.
-
C.
Daniel Blumberg
Daniel Blumberg is a British musician and composer known for his experimental work in indie rock and film scores.
-
D.
Michael Blum
Michael Blum is best known as the husband of comedian and actress Julia Sweeney.
-
E.
Mark Blum
Mark Blum was an American actor known for his work in film, television, and theater, including notable roles in movies like "Desperately Seeking Susan" and "Crocodile Dundee."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2c996c8190a9ebe0e92608feaa |
completed | April 16, 2026, 2:53 a.m. |
Created at: April 10, 2026, 4:16 a.m.