Triple
T21536637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rotters' Club |
E531365
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Kevin Doyle |
—
|
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: Kevin Doyle | Statement: [The Rotters' Club, castMember, Kevin Doyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Doyle Context triple: [The Rotters' Club, castMember, Kevin Doyle]
-
A.
Kevin Doyle
Kevin Doyle is the witty, secretly romantic journalist and love interest of Katherine Heigl’s character in the romantic comedy film "27 Dresses."
-
B.
Kevin Doyle
chosen
Kevin Doyle is a British actor best known for his role as Joseph Molesley in the television series "Downton Abbey."
-
C.
Joe Doyle
Joe Doyle is an actor best known for his role in the supernatural horror television series "Salem."
-
D.
Jake Doyle
Jake Doyle is the wisecracking private investigator protagonist of the Canadian television series "Republic of Doyle," set in St. John’s, Newfoundland.
-
E.
Jimmy Doyle
Jimmy Doyle is a fictional New York City narcotics detective best known as the hard-driving protagonist of the crime film "The French Connection."
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.