Triple
T20283484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Franklin |
E503213
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Don Franklin |
—
|
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: Don Franklin | Statement: [Don Franklin, name, Don Franklin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Franklin Context triple: [Don Franklin, name, Don Franklin]
-
A.
Don Franklin
chosen
Don Franklin is an American actor best known for his roles in science fiction and adventure television series, including a prominent part on SeaQuest DSV.
-
B.
Dean Franklin
Dean Franklin is a screenwriter best known for his work on the classic World War I film "The Fighting 69th."
-
C.
Scott Franklin
Scott Franklin is an American film producer known for his frequent collaborations with director Darren Aronofsky on acclaimed movies such as Black Swan and The Wrestler.
-
D.
Carl Franklin
Carl Franklin is an American actor and acclaimed film and television director known for works such as "One False Move" and "Devil in a Blue Dress."
-
E.
Fred Waller
Fred Waller was an American inventor and film pioneer best known for creating the immersive widescreen Cinerama process that revolutionized cinematic presentation in the mid-20th century.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6769049b48190bc449557b79b9e81 |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 10:48 a.m.