Triple
T19546133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clayton Moore |
E489054
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Clayton Moore |
—
|
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: Clayton Moore | Statement: [Clayton Moore, name, Clayton Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clayton Moore Context triple: [Clayton Moore, name, Clayton Moore]
-
A.
Clayton Moore
chosen
Clayton Moore was an American actor best known for portraying the title character in the classic television series "The Lone Ranger."
-
B.
Randolph Scott
Randolph Scott was a prominent American film actor best known for his roles in Westerns during the 1930s–1950s.
-
C.
Joel McCrea
Joel McCrea was an American film actor best known for his leading roles in classic Hollywood Westerns and comedies from the 1930s through the 1950s.
-
D.
Jack Nance
Jack Nance was an American character actor best known for his longtime collaboration with director David Lynch, including his iconic lead role in the cult film "Eraserhead."
-
E.
James Arness
James Arness was an American actor best known for his long-running role as Marshal Matt Dillon on the television western series "Gunsmoke."
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63876bacc8190b17e2087de679785 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.