Triple
T19742292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Red Line |
E474155
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Noah Wyle |
—
|
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: Noah Wyle | Statement: [The Red Line, stars, Noah Wyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noah Wyle Context triple: [The Red Line, stars, Noah Wyle]
-
A.
Noah Wyle
chosen
Noah Wyle is an American actor best known for his role as Dr. John Carter on the medical drama "ER" and for leading roles in various science fiction and adventure television series and films.
-
B.
John Ehle
John Ehle was an American novelist and screenwriter best known for his historical fiction set in the Appalachian region of North Carolina.
-
C.
Josh Perry
Josh Perry is an actor known for his role in the comedy film "Coffee Town."
-
D.
James Denton
James Denton is an American actor best known for playing plumber Mike Delfino on the television series "Desperate Housewives."
-
E.
Peter Krause
Peter Krause is an American actor best known for his leading roles in television dramas such as Six Feet Under, Sports Night, and Parenthood.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65162382081909bd5a251d7da7f75 |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.