Triple
T20294627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Space Children |
E510114
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Johnny Crawford |
—
|
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: Johnny Crawford | Statement: [The Space Children, hasCastMember, Johnny Crawford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Crawford Context triple: [The Space Children, hasCastMember, Johnny Crawford]
-
A.
Johnny Crawford
chosen
Johnny Crawford was an American actor and singer best known for his role as young Mark McCain on the classic Western television series "The Rifleman."
-
B.
Wally Cox
Wally Cox was an American actor and comedian best known for his mild-mannered, bespectacled persona in film and television during the mid-20th century.
-
C.
Jack Livingston
Jack Livingston was an American silent film actor active in the early 20th century.
-
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.
Donald Bisset
Donald Bisset was a British actor and children's author known for his character roles in film and television as well as his imaginative stories for young readers.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6770714c4819080e3256325747ebf |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:13 a.m.