Triple
T627674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rinko Kikuchi |
E15853
|
entity |
| Predicate | hasGenreSpecialization |
P466
|
FINISHED |
| Object | drama film |
—
|
LITERAL 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: drama film | Statement: [Rinko Kikuchi, hasGenreSpecialization, drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreSpecialization Context triple: [Rinko Kikuchi, hasGenreSpecialization, drama film]
-
A.
hasGenreStrength
Indicates that something possesses a particular intensity or degree of emphasis associated with a specific genre.
-
B.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
hasSpecialSong
Indicates that one entity possesses or is associated with a particular song that is unique, distinctive, or specially designated for it.
-
D.
knownForMusicGenre
Indicates that an entity is recognized or notable for producing, performing, or being associated with a particular music genre.
-
E.
hasTypeGenus
Indicates that one entity is the type genus that formally defines or represents the taxonomic group of the other entity.
- F. None of above.
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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.