Triple
T22394415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Movie in My Mind |
E553592
|
entity |
| Predicate | performedByCharacter |
P14884
|
FINISHED |
| Object | 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: Kim | Statement: [The Movie in My Mind, performedByCharacter, Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Context triple: [The Movie in My Mind, performedByCharacter, Kim]
-
A.
Kim
Kim is a common Korean surname shared by many notable figures in Korean history and contemporary society.
-
B.
Kim
Kim is the commonly used nickname of Kim Philby, the infamous British intelligence officer who became a high-ranking Soviet double agent during the Cold War.
-
C.
Kim
Kim is a common given name used for people of any gender in various cultures, often as a short form of names like Kimberly or Kimball.
-
D.
Kim
"Kim" is a dark, emotionally intense track by Eminem (as Slim Shady) in which he vividly dramatizes a violent confrontation with his then-wife.
-
E.
Kim
Kim is the tragic Vietnamese bar girl and central heroine of the musical "Miss Saigon," whose doomed romance with an American GI drives the story’s emotional core.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585dac3c8190bc221f35b3eefa3f |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.