Triple
T20186338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghostbusters: Frozen Empire |
E492869
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Logan Kim |
—
|
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: Logan Kim | Statement: [Ghostbusters: Frozen Empire, stars, Logan Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logan Kim Context triple: [Ghostbusters: Frozen Empire, stars, Logan Kim]
-
A.
Logan Kim
chosen
Logan Kim is an American child actor best known for his role in the supernatural comedy film "Ghostbusters: Afterlife."
-
B.
Kenny Kim
Kenny Kim is a screenwriter best known for his work on the family martial-arts comedy film "Three Ninjas."
-
C.
Alex Kim
Alex Kim is an astrophysicist known for contributions to observational cosmology and dark energy research as part of the Supernova Cosmology Project.
-
D.
Jason Kim
Jason Kim is a film industry professional known for collaborating with acclaimed South Korean cinematographer Chung Chung-hoon.
-
E.
Jung Kim
Jung Kim is the charismatic and quick-witted convenience store manager and son in the Canadian sitcom "Kim's Convenience."
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad143c48190b9d52c331e8101d6 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:36 p.m.