Triple
T10287154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bud Cort |
E241260
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Bud Cort |
E241260
|
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: Bud Cort | Statement: [Bud Cort, name, Bud Cort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bud Cort Context triple: [Bud Cort, name, Bud Cort]
-
A.
Bud Cort
chosen
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."
-
B.
Jack Elam
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.
-
C.
Aldo Ray
Aldo Ray was an American film actor known for his tough-guy roles and distinctive raspy voice in numerous Hollywood movies of the 1950s and 1960s.
-
D.
Vic Tayback
Vic Tayback was an American actor best known for his Emmy-nominated role as the gruff but lovable diner owner Mel Sharples in the film and television versions of "Alice."
-
E.
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.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b924908190879a7b6b70e0109a |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f84d432c8190a7d33e6c9f8ba8f2 |
completed | April 9, 2026, 12:52 a.m. |
Created at: April 6, 2026, 11:40 a.m.