Triple
T23868265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubo and the Two Strings (film score) |
E592648
|
entity |
| Predicate | filmProductionTechnique |
P2760
|
FINISHED |
| Object | stop-motion |
—
|
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: stop-motion | Statement: [Kubo and the Two Strings (film score), filmProductionTechnique, stop-motion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmProductionTechnique Context triple: [Kubo and the Two Strings (film score), filmProductionTechnique, stop-motion]
-
A.
filmingTechnique
chosen
Indicates the specific method or style used to capture visual content during the filming process.
-
B.
filmmakingTechnology
Indicates the use or involvement of specific tools, methods, or equipment in the process of creating films.
-
C.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
D.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
-
E.
studioFilm
Indicates that a film is produced, distributed, or otherwise created by a particular studio.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cae548dc8190a5f84f2cd7f9778e |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:14 p.m.