Triple
T550564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remote Control Productions |
E11829
|
entity |
| Predicate | hasGenreFocus |
P8464
|
FINISHED |
| Object | orchestral film music |
—
|
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: orchestral film music | Statement: [Remote Control Productions, hasGenreFocus, orchestral film music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreFocus Context triple: [Remote Control Productions, hasGenreFocus, orchestral film music]
-
A.
hasGenreStrength
Indicates that something possesses a particular intensity or degree of emphasis associated with a specific genre.
-
B.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
C.
genreDiversity
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
D.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
E.
hasArtisticGenre
chosen
Indicates that an entity (such as a work or creation) belongs to or is characterized by a particular artistic 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499030cf4819089b9163102255e49 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.