Triple
T18506862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Marshall |
E452218
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object | James Hurley |
—
|
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: James Hurley | Statement: [James Marshall, portrayed, James Hurley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Hurley Context triple: [James Marshall, portrayed, James Hurley]
-
A.
James Hurley
chosen
James Hurley is a brooding, motorcycle-riding young man from the cult TV series "Twin Peaks," known for his romantic entanglements and emotional vulnerability.
-
B.
Jim Hurley
Jim Hurley is a notable individual recognized for achievements significant enough to be associated with the surname Hurley.
-
C.
Gene Harrogate
Gene Harrogate is a comic, hapless young drifter in Cormac McCarthy’s novel "Suttree," known for his bizarre schemes and naive optimism amid the book’s grim setting.
-
D.
Tom Healey
Tom Healey is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the surname Healey.
-
E.
Michael Alldredge
Michael Alldredge was an American character actor known for his supporting roles in films and television during the 1970s and 1980s.
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5334266708190b59aca3a2218c095 |
completed | April 19, 2026, 7:55 p.m. |
Created at: April 10, 2026, 11:36 a.m.