Triple
T22190153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Mosley |
E548398
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Mosley |
—
|
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: Michael Mosley | Statement: [Michael Mosley, name, Michael Mosley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Mosley Context triple: [Michael Mosley, name, Michael Mosley]
-
A.
Michael Mosley
chosen
Michael Mosley is an American actor known for his roles in television series such as "Seven Seconds," "Ozark," and "Scrubs."
-
B.
Michael Mosley
Michael Mosley is a British aristocrat and writer, known as the son of socialite Diana Mitford and politician Sir Oswald Mosley.
-
C.
Michael Begley
Michael Begley is a British actor known for his work in television dramas and comedies, including a role in the series "The Lakes."
-
D.
Jonathan Slavin
Jonathan Slavin is an American actor best known for his comedic television roles, including prominent parts on series like "Dr. Ken" and "Better Off Ted."
-
E.
Jonathan Oppenheim
Jonathan Oppenheim is the son of American actress and comedian Judy Holliday.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aac07d88190848c940863c0a0c7 |
completed | April 28, 2026, 9:46 p.m. |
Created at: April 16, 2026, 8:35 p.m.