Triple
T14841596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Eythe |
E348976
|
entity |
| Predicate | coStarredWith |
P14987
|
FINISHED |
| Object | Charles Bickford |
E135516
|
NE FINISHED |
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: Charles Bickford | Statement: [William Eythe, coStarredWith, Charles Bickford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Bickford Context triple: [William Eythe, coStarredWith, Charles Bickford]
-
A.
Charles Bickford
chosen
Charles Bickford was an American character actor known for his rugged screen presence and acclaimed supporting roles in numerous classic Hollywood films.
-
B.
Hugh Sothern
Hugh Sothern was an American character actor active in early 20th-century stage and film, known for supporting roles in Hollywood movies.
-
C.
Arthur Coburn
Arthur Coburn is a film editor best known for his work on major Hollywood productions, including the action-comedy classic "Beverly Hills Cop."
-
D.
Arthur Coburn
Arthur Coburn is a film editor best known for his work on the 1994 Jim Carrey comedy "The Mask."
-
E.
Arthur Coburn
Arthur Coburn is a film editor best known for his work on the movie "The Cooler."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded28fa49c81908d1059e6cafd607f |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb590b5cc8190b5f586e0fd2988f6 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 1:53 a.m.