Triple
T20681054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Elam |
E508291
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jack Elam |
—
|
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: Jack Elam | Statement: [Jack Elam, name, Jack Elam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Elam Context triple: [Jack Elam, name, Jack Elam]
-
A.
Jack Elam
chosen
Jack Elam was an American character actor best known for his distinctive lazy eye and memorable roles as villains and comic sidekicks in numerous Western films and television series.
-
B.
Phil Kahl
Phil Kahl was a music industry figure best known as a co-founder of the influential American record label Roulette Records.
-
C.
Bud Cort
Bud Cort is an American actor and director best known for his iconic role as the young Harold in the cult classic film "Harold and Maude."
-
D.
Robert Parrish
Robert Parrish was an American film editor and director, as well as a former child actor, known for his work on several classic Hollywood films.
-
E.
Dean Jones
Dean Jones was an American actor best known for his leading roles in numerous Disney live-action films during the 1960s and 1970s.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea655488190bab168d564d888af |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 11:45 a.m.