Triple
T21117091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBGB (film) |
E520326
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Johnny Galecki |
—
|
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 Galecki | Statement: [CBGB (film), stars, Johnny Galecki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Galecki Context triple: [CBGB (film), stars, Johnny Galecki]
-
A.
Johnny Galecki
chosen
Johnny Galecki is an American actor best known for his role as physicist Leonard Hofstadter on the hit sitcom "The Big Bang Theory" and earlier work on the TV series "Roseanne."
-
B.
Robert Sean Leonard
Robert Sean Leonard is an American actor best known for his roles in the television series "House" and films such as "Dead Poets Society."
-
C.
Hugh Dancy
Hugh Dancy is an English actor best known for his role as Will Graham in the television series "Hannibal" and for performances in films such as "Ella Enchanted" and "Confessions of a Shopaholic."
-
D.
Theo James
Theo James is a British actor known for his roles in the Divergent film series and the HBO anthology series The White Lotus.
-
E.
Jack Shepherd
Jack Shepherd is a British actor known for his extensive work in film, television, and theatre, including roles in productions such as "Charlotte Gray."
- 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72106a3b48190a0efa51a74ae21f0 |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:55 p.m.