Triple
T15367589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robots (film score) |
E367456
|
entity |
| Predicate | musicRoleInFilm |
P24740
|
FINISHED |
| Object | supports comedic timing |
—
|
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: supports comedic timing | Statement: [Robots (film score), musicRoleInFilm, supports comedic timing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicRoleInFilm Context triple: [Robots (film score), musicRoleInFilm, supports comedic timing]
-
A.
musicalRole
chosen
Indicates the specific function or part an entity performs within a musical context, such as in a performance, composition, or ensemble.
-
B.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
C.
placementInFilm
Indicates the specific position or occurrence of something within the sequence or structure of a film.
-
D.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
-
E.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4a7cdc8190b7b48c97e774c306 |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca9ab7e88190a9261ef27be665b1 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.